+publisher:"Colorado State University" +contributor:("Pezeshki, Ali")

Colorado State University

1. Wilson, William. Low-noise, low-power transimpedance amplifier for integrated electrochemical biosensor applications.

Degree: MS(M.S.), Electrical and Computer Engineering, 2014, Colorado State University

URL: http://hdl.handle.net/10217/84578

► Biosensor devices have found an increasingly broad range of applications including clinical, biological, and even pharmaceutical research and testing. These devices are useful for detecting… (more)

▼ Biosensor devices have found an increasingly broad range of applications including clinical, biological, and even pharmaceutical research and testing. These devices are useful for detecting chemical compounds in solutions and tissues. Current visual or optical methods include fluorescence and bio/chemiluminescence based detection. These methods involve adding luminescent dyes or fluorescent tags to cells or tissue samples to track movement in response to a stimulus. These methods often harm living tissue and interfere with natural cell movement and function. Electrochemical biosensing methods may be used without adding potentially harmful dyes or chemicals to living tissues. Electrochemical sensing may be used, on the condition that the desired analyte is electrochemically active, and with the assumption that other compounds present are not electrochemically active at the reduction or oxidation potential of the desired analyte. A wide range of analytes can be selectively detected by specifically setting the potential of the solution using a potentiostat. The resulting small-magnitude current must then be converted to a measurable voltage and read using a low-noise transimpedance amplifier. To provide spatial resolution on the intra-cellular level, a large number of electrodes must be used. To measure electrochemical signals in parallel, each electrode requires a minimum of a transimpedance amplifier, as well as other supporting circuitry. Low power consumption is a requirement for the circuitry to avoid generating large amounts of heat, and small size is necessary to limit silicon area. This thesis proposes the design of a low-noise, low-power transimpedance amplifier for application in integrated electrochemical biosensor devices. The final proposed design achieves a 5MΩ transimpedance gain with 981aA/√Hz input inferred noise, 8.06µW at 0.9V power supply, and occupies a silicon area of 0.0074mm2 in a commercial 0.18µm CMOS process. This thesis also explores the development of a multi-channel electrochemical measurement system. Advisors/Committee Members: Chen, Tom (advisor), Pezeshki, Ali (committee member), Henry, Chuck (committee member).

Subjects/Keywords: biosensor; transimpedance; low-power; integrated; electrochemistry

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APA (6^th Edition):

Wilson, W. (2014). Low-noise, low-power transimpedance amplifier for integrated electrochemical biosensor applications. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/84578

Chicago Manual of Style (16^th Edition):

Wilson, William. “Low-noise, low-power transimpedance amplifier for integrated electrochemical biosensor applications.” 2014. Masters Thesis, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/84578.

MLA Handbook (7^th Edition):

Wilson, William. “Low-noise, low-power transimpedance amplifier for integrated electrochemical biosensor applications.” 2014. Web. 17 Jan 2021.

Vancouver:

Wilson W. Low-noise, low-power transimpedance amplifier for integrated electrochemical biosensor applications. [Internet] [Masters thesis]. Colorado State University; 2014. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/84578.

Council of Science Editors:

Wilson W. Low-noise, low-power transimpedance amplifier for integrated electrochemical biosensor applications. [Masters Thesis]. Colorado State University; 2014. Available from: http://hdl.handle.net/10217/84578

Colorado State University

2. Moin, Nabeel. Randomized hierarchical semi-separable structures for parallel direct double-higher-order method of moments.

Degree: MS(M.S.), Electrical and Computer Engineering, 2017, Colorado State University

URL: http://hdl.handle.net/10217/185771

► As technology grows more and more rapidly, the need for large-scale electromagnetics modelling arises. This includes software that can handle very large problems and simulate… (more)

Subjects/Keywords: double-higher-order; hierarchical semi-separable structures; randomized sampling; fast multipole method; computational electromagnetics; method of moments

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APA (6^th Edition):

Moin, N. (2017). Randomized hierarchical semi-separable structures for parallel direct double-higher-order method of moments. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/185771

Chicago Manual of Style (16^th Edition):

Moin, Nabeel. “Randomized hierarchical semi-separable structures for parallel direct double-higher-order method of moments.” 2017. Masters Thesis, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/185771.

MLA Handbook (7^th Edition):

Moin, Nabeel. “Randomized hierarchical semi-separable structures for parallel direct double-higher-order method of moments.” 2017. Web. 17 Jan 2021.

Vancouver:

Moin N. Randomized hierarchical semi-separable structures for parallel direct double-higher-order method of moments. [Internet] [Masters thesis]. Colorado State University; 2017. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/185771.

Council of Science Editors:

Moin N. Randomized hierarchical semi-separable structures for parallel direct double-higher-order method of moments. [Masters Thesis]. Colorado State University; 2017. Available from: http://hdl.handle.net/10217/185771

Colorado State University

3. Smull, Aaron P. Conformal perfectly matched layer for electrically large curvilinear higher order finite element methods in electromagnetics, The.

Degree: MS(M.S.), Electrical and Computer Engineering, 2017, Colorado State University

URL: http://hdl.handle.net/10217/184021

► The implementation of open-region boundary conditions in computational electromagnetics for higher order finite element methods presents a well known set of challenges. One such boundary… (more)

Subjects/Keywords: finite element method; perfectly matched layer; computational electromagnetics; scattering; numerical methods

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APA (6^th Edition):

Smull, A. P. (2017). Conformal perfectly matched layer for electrically large curvilinear higher order finite element methods in electromagnetics, The. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/184021

Chicago Manual of Style (16^th Edition):

Smull, Aaron P. “Conformal perfectly matched layer for electrically large curvilinear higher order finite element methods in electromagnetics, The.” 2017. Masters Thesis, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/184021.

MLA Handbook (7^th Edition):

Smull, Aaron P. “Conformal perfectly matched layer for electrically large curvilinear higher order finite element methods in electromagnetics, The.” 2017. Web. 17 Jan 2021.

Vancouver:

Smull AP. Conformal perfectly matched layer for electrically large curvilinear higher order finite element methods in electromagnetics, The. [Internet] [Masters thesis]. Colorado State University; 2017. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/184021.

Council of Science Editors:

Smull AP. Conformal perfectly matched layer for electrically large curvilinear higher order finite element methods in electromagnetics, The. [Masters Thesis]. Colorado State University; 2017. Available from: http://hdl.handle.net/10217/184021

Colorado State University

4. Kopacz, Justin. Optimal dictionary learning with application to underwater target detection from synthetic aperture sonar imagery.

Degree: MS(M.S.), Electrical and Computer Engineering, 2014, Colorado State University

URL: http://hdl.handle.net/10217/82647

► K-SVD is a relatively new method used to create a dictionary matrix that best ts a set of training data vectors formed with the intent… (more)

▼ K-SVD is a relatively new method used to create a dictionary matrix that best ts a set of training data vectors formed with the intent of using it for sparse representation of a data vector. K-SVD is flexible in that it can be used in conjunction with any preferred pursuit method of sparse coding including the orthogonal matching pursuit (OMP) method considered in this thesis. Using adaptive lter theory, a new fast OMP method has been proposed to reduce the computational time of the sparse pursuit phase of K-SVD as well as during on-line implementation without sacrificing the accuracy of the sparse pursuit method. Due to the matrix inversion required in the standard OMP, the amount of time required to sparsely represent a signal grows quickly as the sparsity restriction is relaxed. The speed up in the proposed method was accomplished by replacing this computationally demanding matrix inversion with a series of recursive "time-order" update equations by using orthogonal projection updating used in adaptive filter theory. The geometric perspective of this new learning is also provided. Additionally, a recursive method for faster dictionary learning is also discussed which can be used instead of the singular value decomposition (SVD) process in the K-SVD method. A significant bottleneck in K-SVD is the computation of the SVD of the reduced error matrix during the update of each dictionary atom. The SVD operation is replaced with an efficient recursive update which will allow limited in-situ learning to update dictionaries as the system is exposed to new signals. Further, structured data formatting has allowed a multi-channel extension of K-SVD to merge multiple data sources into a single dictionary capable of creating a single sparse vector representing a variety of multi-channel data. Another contribution of this work is the application of the developed methods to an underwater target detection problem using coregistered dual-channel (namely broadband and high-frequency) side-scan sonar imagery data. Here, K-SVD is used to create a more optimal dictionary in the sense of reconstructing target and non-target image snippets using their respective dictionaries. The ratio of the reconstruction errors is used as a likelihood ratio for target detection. The proposed methods were then applied and benchmarked against other detection methods for detecting mine-like objects from two dual-channel sonar datasets. Comparison of the results in terms of receiver operating characteristic (ROC) curve indicates that the dual-channel K-SVD based detector provides a detection rate of PD = 99% and false alarms rate of PFA = 1% on the first dataset, and PD = 95% and PFA = 5% on the second dataset at the knee point of the ROC. The single-channel K-SVD based detector on the other hand, provides PD = 96% and PFA = 4% on the first dataset, and PD = 96% and PFA = 4% on the second dataset at the knee point of the ROC. The degradation in performance for the second dataset is attributed to the fact that the system was trained on a limited… Advisors/Committee Members: Azimi-Sadjadi, Mahmood R. (advisor), Pezeshki, Ali (committee member), Breidt, Jay (committee member).

Subjects/Keywords: dictionary learning; underwater target detection; sparse coding; orthogonal matching pursuit; K-SVD

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Kopacz, J. (2014). Optimal dictionary learning with application to underwater target detection from synthetic aperture sonar imagery. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/82647

Chicago Manual of Style (16^th Edition):

Kopacz, Justin. “Optimal dictionary learning with application to underwater target detection from synthetic aperture sonar imagery.” 2014. Masters Thesis, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/82647.

MLA Handbook (7^th Edition):

Kopacz, Justin. “Optimal dictionary learning with application to underwater target detection from synthetic aperture sonar imagery.” 2014. Web. 17 Jan 2021.

Vancouver:

Kopacz J. Optimal dictionary learning with application to underwater target detection from synthetic aperture sonar imagery. [Internet] [Masters thesis]. Colorado State University; 2014. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/82647.

Council of Science Editors:

Kopacz J. Optimal dictionary learning with application to underwater target detection from synthetic aperture sonar imagery. [Masters Thesis]. Colorado State University; 2014. Available from: http://hdl.handle.net/10217/82647

Colorado State University

5. Yi, Zhangjing. Characterization of a photoluminescence-based fiber optic sensor system.

Degree: MS(M.S.), Electrical and Computer Engineering, 2011, Colorado State University

URL: http://hdl.handle.net/10217/70840

► Measuring multiple analyte concentrations is essential for a wide range of environmental applications, which are important for the pursuit of public safety and health. Target… (more)

▼ Measuring multiple analyte concentrations is essential for a wide range of environmental applications, which are important for the pursuit of public safety and health. Target analytes are often toxic chemical compounds found in groundwater or soil. However, in-situ measurement of such analytes still faces various challenges. Some of these challenges are rapid response for near-real time monitoring, simultaneous measurements of multiple analytes in a complex target environment, and high sensitivity for low analyte concentration without sample pretreatment. This thesis presents a low-cost, robust, multichannel fiber optic photoluminescence (PL)-based sensor system using a time-division multiplexing architecture for multiplex biosensor arrays for in-situ measurements in environmental applications. The system was designed based upon an indirect sensing scheme with a pH or oxygen sensitive dye molecules working as the transducer that is easily adaptable with various enzymes for detecting different analytes. A characterization of the multi-channel fiber optic PL-based sensor system was carried out in this thesis. Experiments were designed with interests in investigating this system's performance with only the transducer thus providing reference figures of merit, such as sensitivity and limit of detection, for further experiments or applications with the addition of various biosensors. A pH sensitive dye, fluoresceinamine (FLA), used as the transducer is immobilized in a poly vinyl alcohol (PVA) matrix for the characterization. The system exhibits a sensitivity of 8.66×10 5 M -1 as the Stern-Volmer constant, K SV , in H + concentration measurement range of 0.002 - 891 μM (pH of 3.05 - 8.69). A mathematical model is introduced to describe the Stern-Volmer equation's non-idealities, which are fluorophore fractional accessibility and the back reflection. Channel-to-channel uniformity is characterized with the modified Stern-Volmer model. Combining the FLA with appropriate enzymatic biosensors, the system is capable of 1,2-dichloroethane (DCA) and ethylene dibromide (EDB) detection. The calculated limit of detection (LOD) of the system can be as low as 0.08 μg/L for DCA and 0.14 μg/L for EDB. The performances of fused fiber coupler and bifurcated fiber assembly were investigated for the application in the fiber optic PL-based sensor systems in this thesis. Complex tradeoffs among back reflection noise, coupling efficiency and split ratio were analyzed with theoretical and experimental data. A series of experiments and simulations were carried out to compare the two types of fiber assemblies in the PL-based sensor systems in terms of excess loss, split ratio, back reflection, and coupling efficiency. A noise source analysis of three existing PL-intensity-based fiber optic enzymatic biosensor systems is provided to reveal the power distribution of different noise components. The three systems are a single channel system with a spectrometer as the detection device, a lab-developed multi-channel system, and a commercial prototype… Advisors/Committee Members: Lear, Kevin L. (advisor), Pezeshki, Ali (committee member), Mueller, Jennifer L. (committee member).

Subjects/Keywords: biosensor; Stern-Volmer; photoluminescence; fiber optic; enzyme

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APA (6^th Edition):

Yi, Z. (2011). Characterization of a photoluminescence-based fiber optic sensor system. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/70840

Chicago Manual of Style (16^th Edition):

Yi, Zhangjing. “Characterization of a photoluminescence-based fiber optic sensor system.” 2011. Masters Thesis, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/70840.

MLA Handbook (7^th Edition):

Yi, Zhangjing. “Characterization of a photoluminescence-based fiber optic sensor system.” 2011. Web. 17 Jan 2021.

Vancouver:

Yi Z. Characterization of a photoluminescence-based fiber optic sensor system. [Internet] [Masters thesis]. Colorado State University; 2011. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/70840.

Council of Science Editors:

Yi Z. Characterization of a photoluminescence-based fiber optic sensor system. [Masters Thesis]. Colorado State University; 2011. Available from: http://hdl.handle.net/10217/70840

Colorado State University

6. Dhanapala, Dulanjalie C. Anchor centric virtual coordinate systems in wireless sensor networks: from self-organization to network awareness.

Degree: PhD, Electrical and Computer Engineering, 2012, Colorado State University

URL: http://hdl.handle.net/10217/71554

► Future Wireless Sensor Networks (WSNs) will be collections of thousands to millions of sensor nodes, automated to self-organize, adapt, and collaborate to facilitate distributed monitoring… (more)

▼ Future Wireless Sensor Networks (WSNs) will be collections of thousands to millions of sensor nodes, automated to self-organize, adapt, and collaborate to facilitate distributed monitoring and actuation. They may even be deployed over harsh geographical terrains and 3D structures. Low-cost sensor nodes that facilitate such massive scale networks have stringent resource constraints (e.g., in memory and energy) and limited capabilities (e.g., in communication range and computational power). Economic constraints exclude the use of expensive hardware such as Global Positioning Systems (GPSs) for network organization and structuring in many WSN applications. Alternatives that depend on signal strength measurements are highly sensitive to noise and fading, and thus often are not pragmatic for network organization. Robust, scalable, and efficient algorithms for network organization and reliable information exchange that overcome the above limitations without degrading the network's lifespan are vital for facilitating future large-scale WSN networks. This research develops fundamental algorithms and techniques targeting self-organization, data dissemination, and discovery of physical properties such as boundaries of large-scale WSNs without the need for costly physical position information. Our approach is based on Anchor Centric Virtual Coordinate Systems, commonly called Virtual Coordinate Systems (VCSs), in which each node is characterized by a coordinate vector of shortest path hop distances to a set of anchor nodes. We develop and evaluate algorithms and techniques for the following tasks associated with use of VCSs in WSNs: (a) novelty analysis of each anchor coordinate and compressed representation of VCSs; (b) regaining lost directionality and identifying a 'good' set of anchors; (c) generating topology preserving maps (TPMs); (d) efficient and reliable data dissemination, and boundary identification without physical information; and (f) achieving network awareness at individual nodes. After investigating properties and issues related to VCS, a Directional VCS (DVCS) is proposed based on a novel transformation that restores the lost directionality information in VCS. Extreme Node Search (ENS), a novel and efficient anchor placement scheme, starts with two randomly placed anchors and then uses this directional transformation to identify the number and placement of anchors in a completely distributed manner. Furthermore, a novelty-filtering-based approach for identifying a set of 'good' anchors that reduces the overhead and power consumption in routing is discussed. Physical layout information such as physical voids and even relative physical positions of sensor nodes with respect to X-Y directions are absent in a VCS description. Obtaining such information independent of physical information or signal strength measurements has not been possible until now. Two novel techniques to extract Topology Preserving Maps (TPMs) from VCS, based on Singular Value Decomposition (SVD) and DVCS are presented. A TPM is a distorted… Advisors/Committee Members: Jayasumana, Anura P. (advisor), Kirby, Michael (committee member), Pezeshki, Ali (committee member), Ray, Indrakshi (committee member).

Subjects/Keywords: network awareness; phenomena discovery; routing; sensor networks; topology preserving maps; virtual coordinate systems

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APA (6^th Edition):

Dhanapala, D. C. (2012). Anchor centric virtual coordinate systems in wireless sensor networks: from self-organization to network awareness. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/71554

Chicago Manual of Style (16^th Edition):

Dhanapala, Dulanjalie C. “Anchor centric virtual coordinate systems in wireless sensor networks: from self-organization to network awareness.” 2012. Doctoral Dissertation, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/71554.

MLA Handbook (7^th Edition):

Dhanapala, Dulanjalie C. “Anchor centric virtual coordinate systems in wireless sensor networks: from self-organization to network awareness.” 2012. Web. 17 Jan 2021.

Vancouver:

Dhanapala DC. Anchor centric virtual coordinate systems in wireless sensor networks: from self-organization to network awareness. [Internet] [Doctoral dissertation]. Colorado State University; 2012. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/71554.

Council of Science Editors:

Dhanapala DC. Anchor centric virtual coordinate systems in wireless sensor networks: from self-organization to network awareness. [Doctoral Dissertation]. Colorado State University; 2012. Available from: http://hdl.handle.net/10217/71554

Colorado State University

7. Zhang, Wenshu. Cooperative sensing for target estimation and target localization.

Degree: PhD, Electrical and Computer Engineering, 2011, Colorado State University

URL: http://hdl.handle.net/10217/70658

► As a novel sensing scheme, cooperative sensing has drawn great interests in recent years. By utilizing the concept of "cooperation", which incorporates communications and information… (more)

▼ As a novel sensing scheme, cooperative sensing has drawn great interests in recent years. By utilizing the concept of "cooperation", which incorporates communications and information exchanges among multiple sensing devices, e.g. radar transceivers in radar systems, sensor nodes in wireless sensor networks, or mobile handsets in cellular systems, the sensing capability can achieve significant improvement compared to the conventional noncooperative mode in many aspects. For example, cooperative target estimation is inspired by the benefits of MIMO in communications, where multiple transmit and/or receive antennas can increase the diversity to combat channel fading for enhanced transmission reliability and increase the degrees of freedom for improved data rate. On the other hand, cooperative target localization is able to dramatically increase localization performance in terms of both accuracy and coverage. From the perspective of cooperative target estimation, in this dissertation, we optimize waveforms from multiple cooperative transmitters to facilitate better target estimation in the presence of colored noise. We introduce the normalized MSE (NMSE) minimizing criterion for radar waveform designs. Not only is it more meaningful for parameter estimation problems, but it also exhibits more similar behaviors with the MI criterion than its MMSE counterpart. We also study the robust designs for both the probing waveforms at the transmitter and the estimator at the receiver to address one type of a priori information uncertainties, i.e., in-band target and noise PSD uncertainties. The relationship between MI and MSEs is further investigated through analysis of the sensitivity of the optimum design to the out-band PSD uncertainties as known as the overestimation error. From the perspective of cooperative target localization, in this dissertation, we study the two phases that comprise a localization process, i.e., the distance measurement phase and the location update phase. In the first distance measurement phase, thanks to UWB signals' many desirable features including high delay resolution and obstacle penetration capabilities, we adopt UWB technology for TOA estimation, and then translate the TOA estimate into distance given light propagation speed. We develop a practical data-aided ML timing algorithm and obtain its optimum training sequence. Based on this optimum sequence, the original ML algorithm can be simplified without affecting its optimality. In the second location update phase, we investigate secure cooperative target localization in the presence of malicious attacks, which consists of a fundamental issue in localization problems. We explicitly incorporate anchors' misplacements into distance measurement model and explore the pairwise sparse nature of the misplacements. We formulate the secure localization problem as an ℓ1-regularized least squares (LS) problem and establish the pairwise sparsity upper bound which defines the largest possible number of identifiable malicious anchors. Particularly, it is… Advisors/Committee Members: Yang, Liuqing (advisor), Pezeshki, Ali (committee member), Luo, J. Rockey (committee member), Wang, Haonan (committee member).

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APA (6^th Edition):

Zhang, W. (2011). Cooperative sensing for target estimation and target localization. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/70658

Chicago Manual of Style (16^th Edition):

Zhang, Wenshu. “Cooperative sensing for target estimation and target localization.” 2011. Doctoral Dissertation, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/70658.

MLA Handbook (7^th Edition):

Zhang, Wenshu. “Cooperative sensing for target estimation and target localization.” 2011. Web. 17 Jan 2021.

Vancouver:

Zhang W. Cooperative sensing for target estimation and target localization. [Internet] [Doctoral dissertation]. Colorado State University; 2011. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/70658.

Council of Science Editors:

Zhang W. Cooperative sensing for target estimation and target localization. [Doctoral Dissertation]. Colorado State University; 2011. Available from: http://hdl.handle.net/10217/70658

Colorado State University

8. Kern, Tucker. Design of integrated on-chip impedance sensors.

Degree: MS(M.S.), Electrical and Computer Engineering, 2014, Colorado State University

URL: http://hdl.handle.net/10217/83982

► In this thesis two integrated sensor systems for measuring the impedance of a device under test (DUT) are presented. Both sensors have potential applications in… (more)

Subjects/Keywords: CMOS; sensor; impedance

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APA (6^th Edition):

Kern, T. (2014). Design of integrated on-chip impedance sensors. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/83982

Chicago Manual of Style (16^th Edition):

Kern, Tucker. “Design of integrated on-chip impedance sensors.” 2014. Masters Thesis, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/83982.

MLA Handbook (7^th Edition):

Kern, Tucker. “Design of integrated on-chip impedance sensors.” 2014. Web. 17 Jan 2021.

Vancouver:

Kern T. Design of integrated on-chip impedance sensors. [Internet] [Masters thesis]. Colorado State University; 2014. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/83982.

Council of Science Editors:

Kern T. Design of integrated on-chip impedance sensors. [Masters Thesis]. Colorado State University; 2014. Available from: http://hdl.handle.net/10217/83982

Colorado State University

9. Yaremenko, Vladimir. Unattended acoustic sensor systems for noise monitoring in national parks.

Degree: MS(M.S.), Electrical and Computer Engineering, 2017, Colorado State University

URL: http://hdl.handle.net/10217/181332

► Detection and classification of transient acoustic signals is a difficult problem. The problem is often complicated by factors such as the variety of sources that… (more)

▼ Detection and classification of transient acoustic signals is a difficult problem. The problem is often complicated by factors such as the variety of sources that may be encountered, the presence of strong interference and substantial variations in the acoustic environment. Furthermore, for most applications of transient detection and classification, such as speech recognition and environmental monitoring, online detection and classification of these transient events is required. This is even more crucial for applications such as environmental monitoring as it is often done at remote locations where it is unfeasible to set up a large, general-purpose processing system. Instead, some type of custom-designed system is needed which is power efficient yet able to run the necessary signal processing algorithms in near real-time. In this thesis, we describe a custom-designed environmental monitoring system (EMS) which was specifically designed for monitoring air traffic and other sources of interest in national parks. More specifically, this thesis focuses on the capabilities of the EMS and how transient detection, classification and tracking are implemented on it. The Sparse Coefficient State Tracking (SCST) transient detection and classification algorithm was implemented on the EMS board in order to detect and classify transient events. This algorithm was chosen because it was designed for this particular application and was shown to have superior performance compared to other algorithms commonly used for transient detection and classification. The SCST algorithm was implemented on an Artix 7 FPGA with parts of the algorithm running as dedicated custom logic and other parts running sequentially on a soft-core processor. In this thesis, the partitioning and pipelining of this algorithm is explained. Each of the partitions was tested independently to very their functionality with respect to the overall system. Furthermore, the entire SCST algorithm was tested in the field on actual acoustic data and the performance of this implementation was evaluated using receiver operator characteristic (ROC) curves and confusion matrices. In this test the FPGA implementation of SCST was able to achieve acceptable source detection and classification results despite a difficult data set and limited training data. The tracking of acoustic sources is done through successive direction of arrival (DOA) angle estimation using a wideband extension of the Capon beamforming algorithm. This algorithm was also implemented on the EMS in order to provide real-time DOA estimates for the detected sources. This algorithm was partitioned into several stages with some stages implemented in custom logic while others were implemented as software running on the soft-core processor. Just as with SCST, each partition of this beamforming algorithm was verified independently and then a full system test was conducted to evaluate whether it would be able to track an airborne source. For the full system test, a model airplane was flown at various trajectories… Advisors/Committee Members: Azimi-Sadjadi, Mahmood R. (advisor), Pezeshki, Ali (committee member), Anderson, Charles (committee member).

Subjects/Keywords: noise monitoring; statistical signal processing; embedded systems; transient signals; remote sensing

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APA (6^th Edition):

Yaremenko, V. (2017). Unattended acoustic sensor systems for noise monitoring in national parks. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/181332

Chicago Manual of Style (16^th Edition):

Yaremenko, Vladimir. “Unattended acoustic sensor systems for noise monitoring in national parks.” 2017. Masters Thesis, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/181332.

MLA Handbook (7^th Edition):

Yaremenko, Vladimir. “Unattended acoustic sensor systems for noise monitoring in national parks.” 2017. Web. 17 Jan 2021.

Vancouver:

Yaremenko V. Unattended acoustic sensor systems for noise monitoring in national parks. [Internet] [Masters thesis]. Colorado State University; 2017. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/181332.

Council of Science Editors:

Yaremenko V. Unattended acoustic sensor systems for noise monitoring in national parks. [Masters Thesis]. Colorado State University; 2017. Available from: http://hdl.handle.net/10217/181332

Colorado State University

10. Ahadi Dolatsara, Majid. Efficient multidimensional uncertainty quantification of high speed circuits using advanced polynomial chaos approaches.

Degree: MS(M.S.), Electrical and Computer Engineering, 2016, Colorado State University

URL: http://hdl.handle.net/10217/176722

► With the scaling of VLSI technology to sub-45 nm levels, uncertainty in the nanoscale manufacturing processes and operating conditions have been found to result in… (more)

Subjects/Keywords: high speed circuits; polynomial chaos; uncertainty quantification; linear regression; computer aided design; signal integrity

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APA (6^th Edition):

Ahadi Dolatsara, M. (2016). Efficient multidimensional uncertainty quantification of high speed circuits using advanced polynomial chaos approaches. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/176722

Chicago Manual of Style (16^th Edition):

Ahadi Dolatsara, Majid. “Efficient multidimensional uncertainty quantification of high speed circuits using advanced polynomial chaos approaches.” 2016. Masters Thesis, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/176722.

MLA Handbook (7^th Edition):

Ahadi Dolatsara, Majid. “Efficient multidimensional uncertainty quantification of high speed circuits using advanced polynomial chaos approaches.” 2016. Web. 17 Jan 2021.

Vancouver:

Ahadi Dolatsara M. Efficient multidimensional uncertainty quantification of high speed circuits using advanced polynomial chaos approaches. [Internet] [Masters thesis]. Colorado State University; 2016. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/176722.

Council of Science Editors:

Ahadi Dolatsara M. Efficient multidimensional uncertainty quantification of high speed circuits using advanced polynomial chaos approaches. [Masters Thesis]. Colorado State University; 2016. Available from: http://hdl.handle.net/10217/176722

Colorado State University

11. Kleinkort, Cameron. Visual hull method for realistic 3D particle shape reconstruction based on high-resolution photographs of snowflakes in freefall from multiple views.

Degree: MS(M.S.), Electrical and Computer Engineering, 2016, Colorado State University

URL: http://hdl.handle.net/10217/176670

► Proposed and presented is a visual hull method and technique for reconstruction of realistic 3D shapes of snowflakes and other hydrometeors based on high-resolution photographs… (more)

Subjects/Keywords: computational electromagnetics; snowflakes; visual hull; radar; 3D reconstruction; snow microphysics

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APA (6^th Edition):

Kleinkort, C. (2016). Visual hull method for realistic 3D particle shape reconstruction based on high-resolution photographs of snowflakes in freefall from multiple views. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/176670

Chicago Manual of Style (16^th Edition):

Kleinkort, Cameron. “Visual hull method for realistic 3D particle shape reconstruction based on high-resolution photographs of snowflakes in freefall from multiple views.” 2016. Masters Thesis, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/176670.

MLA Handbook (7^th Edition):

Kleinkort, Cameron. “Visual hull method for realistic 3D particle shape reconstruction based on high-resolution photographs of snowflakes in freefall from multiple views.” 2016. Web. 17 Jan 2021.

Vancouver:

Kleinkort C. Visual hull method for realistic 3D particle shape reconstruction based on high-resolution photographs of snowflakes in freefall from multiple views. [Internet] [Masters thesis]. Colorado State University; 2016. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/176670.

Council of Science Editors:

Kleinkort C. Visual hull method for realistic 3D particle shape reconstruction based on high-resolution photographs of snowflakes in freefall from multiple views. [Masters Thesis]. Colorado State University; 2016. Available from: http://hdl.handle.net/10217/176670

Colorado State University

12. Mellenthin, Michelle M. Active complex electrode (ACE1) electrical impedance tomography system & anatomically inspired modeling of electrode-skin contact impedance, The.

Degree: PhD, Bioengineering, 2016, Colorado State University

URL: http://hdl.handle.net/10217/176717

► Electrical Impedance Tomography (EIT) is a technique used to image the varying electrical properties of biological tissues or tissue conductivity and permittivity. There are many… (more)

Subjects/Keywords: EIT; impedance; tomography; electrical; contact; system

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APA (6^th Edition):

Mellenthin, M. M. (2016). Active complex electrode (ACE1) electrical impedance tomography system & anatomically inspired modeling of electrode-skin contact impedance, The. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/176717

Chicago Manual of Style (16^th Edition):

Mellenthin, Michelle M. “Active complex electrode (ACE1) electrical impedance tomography system & anatomically inspired modeling of electrode-skin contact impedance, The.” 2016. Doctoral Dissertation, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/176717.

MLA Handbook (7^th Edition):

Mellenthin, Michelle M. “Active complex electrode (ACE1) electrical impedance tomography system & anatomically inspired modeling of electrode-skin contact impedance, The.” 2016. Web. 17 Jan 2021.

Vancouver:

Mellenthin MM. Active complex electrode (ACE1) electrical impedance tomography system & anatomically inspired modeling of electrode-skin contact impedance, The. [Internet] [Doctoral dissertation]. Colorado State University; 2016. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/176717.

Council of Science Editors:

Mellenthin MM. Active complex electrode (ACE1) electrical impedance tomography system & anatomically inspired modeling of electrode-skin contact impedance, The. [Doctoral Dissertation]. Colorado State University; 2016. Available from: http://hdl.handle.net/10217/176717

Colorado State University

13. Wachowski, Neil. Characterization of multiple time-varying transient sources from multivariate data sequences.

Degree: PhD, Electrical and Computer Engineering, 2014, Colorado State University

URL: http://hdl.handle.net/10217/82575

► Characterization of multiple time-varying transient sources using sequential multivariate data is a broad and complex signal processing problem. In general, this process involves analyzing new… (more)

▼ Characterization of multiple time-varying transient sources using sequential multivariate data is a broad and complex signal processing problem. In general, this process involves analyzing new observation vectors in a data stream of unknown length to determine if they contain the signatures of a source of interest (i.e., a signal), in which case the source's type and interference-free signatures may be estimated. This process may continue indefinitely to detect and classify several events of interest thereby yielding an aggregate description of the data's contents. Such capabilities are useful in numerous applications that involve continuously observing an environment containing complicated and erratic signals, e.g., habitat monitoring using acoustical data, medical diagnosis via magnetic resonance imaging, and underwater mine hunting using sonar imagery. The challenges associated with successful transient source characterization are as numerous as the application areas, and include 1) significant variations among signatures emitted by a given source type, 2) the presence of multiple types of random yet structured interference sources whose signatures are superimposed with those of signals, 3) a data representation that is not necessarily optimized for the task at hand, 4) variable environmental and operating conditions, and many others. These challenges are compounded by the inherent difficulties associated with processing sequential multivariate data, namely the inability to exploit the statistics or structure of the entire data stream. On the other hand, the complications that must be addressed often vary significantly when considering different types of data, leading to an abundance of existing solutions that are each specialized for a particular application. In other words, most existing work only simultaneously considers a subset of these complications, making them difficult to generalize. The work in this thesis was motivated by an application involving characterization of national park soundscapes in terms of commonly occurring man-made and natural acoustical sources, using streams of "1/3 octave vector'' sequences. Naturally, this application involves developing solutions that consider all of the mentioned challenges, among others. Two comprehensive solutions to this problem were developed, each with unique strengths and weaknesses relative to one another. A sequential random coefficient tracking (SRCT) method was developed first, that hierarchically applies a set of likelihood ratio tests to each incoming vector observation to detect and classify up to one signal and one interference source that may be simultaneously present. Since the signatures of each acoustical event typically span several adjacent observations, a Kalman filter is used to generate the parameters necessary for computing the likelihood values. The SRCT method is also capable of using the coefficient estimates produced by the Kalman filter to generate estimates of both the signal and interference components of the observation, thus… Advisors/Committee Members: Azimi-Sadjadi, Mahmood R. (advisor), Breidt, F. Jay (committee member), Fristrup, Kurt (committee member), Pezeshki, Ali (committee member).

Subjects/Keywords: acoustical sources; transient detection; signal classification; multivariate analysis

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APA (6^th Edition):

Wachowski, N. (2014). Characterization of multiple time-varying transient sources from multivariate data sequences. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/82575

Chicago Manual of Style (16^th Edition):

Wachowski, Neil. “Characterization of multiple time-varying transient sources from multivariate data sequences.” 2014. Doctoral Dissertation, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/82575.

MLA Handbook (7^th Edition):

Wachowski, Neil. “Characterization of multiple time-varying transient sources from multivariate data sequences.” 2014. Web. 17 Jan 2021.

Vancouver:

Wachowski N. Characterization of multiple time-varying transient sources from multivariate data sequences. [Internet] [Doctoral dissertation]. Colorado State University; 2014. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/82575.

Council of Science Editors:

Wachowski N. Characterization of multiple time-varying transient sources from multivariate data sequences. [Doctoral Dissertation]. Colorado State University; 2014. Available from: http://hdl.handle.net/10217/82575

Colorado State University

14. Dahlke, Mark. Survey sampling with nonparametric methods: endogenous post-stratification and penalized instrumental variables.

Degree: PhD, Statistics, 2012, Colorado State University

URL: http://hdl.handle.net/10217/67995

► Two topics related to the common theme of nonparametric techniques in survey sampling are examined. The first topic explores the estimation of a finite population… (more)

▼ Two topics related to the common theme of nonparametric techniques in survey sampling are examined. The first topic explores the estimation of a finite population mean via post-stratification. Post-stratification is used to improve the precision of survey estimators when categorical auxiliary information is available from external sources. In natural resource surveys, such information may be obtained from remote sensing data classified into categories and displayed as maps. These maps may be based on classification models fitted to the sample data. Such "endogenous post-stratification" violates the standard assumptions that observations are classified without error into post-strata, and post-stratum population counts are known. Properties of the endogenous post-stratification estimator (EPSE) are derived for the case of sample-fitted nonparametric models, with particular emphasis on monotone regression models. Asymptotic properties of the nonparametric EPSE are investigated under a superpopulation model framework. Simulation experiments illustrate the practical effects of first fitting a nonparametric model to survey data before post-stratifying. The second topic explores the use of instrumental variables to estimate regression coefficients. Informative sampling in survey problems occurs when the inclusion probabilities depend on the values of the study variable. In a regression setting under this sampling scheme, ordinary least squares estimators are biased and inconsistent. Given inverse inclusion probabilities as weights for the sample, various consistent estimators can be constructed. In particular, weighted covariates can be used as instrumental variables, allowing for calculation of a consistent, classical two-stage least squares estimator. The proposed estimator uses a similar two-stage process, but with penalized splines at the first stage. Consistency and asymptotic normality of the new estimator are established. The estimator is asymptotically unbiased, but has a finite-sample bias that is analytically characterized. Selection of an optimal smoothing parameter is shown to reduce the finite-sample variance, in comparison to that of the classical two-stage least squares estimator, offsetting the bias and providing an estimator with a reduced mean square error. Advisors/Committee Members: Breidt, F. Jay (advisor), Opsomer, Jean (committee member), Lee, Myung-Hee (committee member), Pezeshki, Ali (committee member).

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Dahlke, M. (2012). Survey sampling with nonparametric methods: endogenous post-stratification and penalized instrumental variables. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/67995

Chicago Manual of Style (16^th Edition):

Dahlke, Mark. “Survey sampling with nonparametric methods: endogenous post-stratification and penalized instrumental variables.” 2012. Doctoral Dissertation, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/67995.

MLA Handbook (7^th Edition):

Dahlke, Mark. “Survey sampling with nonparametric methods: endogenous post-stratification and penalized instrumental variables.” 2012. Web. 17 Jan 2021.

Vancouver:

Dahlke M. Survey sampling with nonparametric methods: endogenous post-stratification and penalized instrumental variables. [Internet] [Doctoral dissertation]. Colorado State University; 2012. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/67995.

Council of Science Editors:

Dahlke M. Survey sampling with nonparametric methods: endogenous post-stratification and penalized instrumental variables. [Doctoral Dissertation]. Colorado State University; 2012. Available from: http://hdl.handle.net/10217/67995

Colorado State University

15. Tabaghi, Puoya. Mixture of factor models for joint dimensionality reduction and classification.

Degree: MS(M.S.), Electrical and Computer Engineering, 2016, Colorado State University

URL: http://hdl.handle.net/10217/176735

► In many areas such as machine learning, pattern recognition, information retrieval, and data mining one is interested in extracting a low-dimensional data that is truly… (more)

▼ In many areas such as machine learning, pattern recognition, information retrieval, and data mining one is interested in extracting a low-dimensional data that is truly representative of the properties of the original high dimensional data. For example, one application could be extracting representative low-dimensional features of underwater objects from sonar imagery suitable for detection and classiﬁcation. This is a diﬃcult problem due to various factors such as variations in the operating and environmental conditions, presence of spatially varying clutter, and variations in object shapes, compositions, and orientation. The goal of this work is to develop a novel probabilistic method using a mixture of factor models for simultaneous nonlinear dimensionality reduction and classiﬁcation. The framework used here is inspired by the work in [1] which uses a mixture of local PCA projections leading to an unsupervised nonlinear dimensionality reduction algorithm. In contrast, the proposed method provides a supervised probabilistic approach suitable for analyzing labeled high-dimensional data with complex structures by exploiting a set of low-dimensional latent variables which are both discriminative and generative. With the aid of these low-dimensional latent variables, a mixture of linear models is introduced to represent the high-dimensional data. An optimum linear classiﬁer is then built in the latent variable-domain to separate the support of the latent variable associated with each class. Introducing these hidden variables allow us to derive the joint probability density function of the data and class label, reduce data dimension and perform clustering, classiﬁcation and parameter estimation. This probabilistic approach provides a mechanism to traverse between the input space and latent (feature) space and vice versa as well as cluster and classify data. A supervised training based on the Expectation-Maximization (EM) and steepest descent algorithms is then introduced to derive the ML estimates of the unknown parameters. It is shown that parameters associated with dimensionality reduction can be estimated using the EM algorithm whereas those of the classiﬁer are estimated using the steepest descent method. The introduction of latent variables not only helps to represent the pdf of data and reduce the dimension of them but also in parameter estimation using EM algorithm which is used to ﬁnd ML estimates of the parameters when the available data is incomplete. A comprehensive study is carried out to assess the performance of the proposed method using two diﬀerent data sets. The ﬁrst data set consists of Synthetic Aperture Sonar (SAS) images of model-generated underwater objects superimposed on background clutter. These images correspond to two diﬀerent object types namely Cylinder (mine-like) and Block (non-mine-like). The signatures of each object are synthetically generated and are placed at various aspect angles from 1 to 180 degrees for each object type. The goal of our classiﬁer is to assign non-target versus… Advisors/Committee Members: Azimi-Sadjadi, Mahmood R. (advisor), Scharf, Louis L. (advisor), Pezeshki, Ali (committee member), Kirby, Michael (committee member).

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APA (6^th Edition):

Tabaghi, P. (2016). Mixture of factor models for joint dimensionality reduction and classification. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/176735

Chicago Manual of Style (16^th Edition):

Tabaghi, Puoya. “Mixture of factor models for joint dimensionality reduction and classification.” 2016. Masters Thesis, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/176735.

MLA Handbook (7^th Edition):

Tabaghi, Puoya. “Mixture of factor models for joint dimensionality reduction and classification.” 2016. Web. 17 Jan 2021.

Vancouver:

Tabaghi P. Mixture of factor models for joint dimensionality reduction and classification. [Internet] [Masters thesis]. Colorado State University; 2016. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/176735.

Council of Science Editors:

Tabaghi P. Mixture of factor models for joint dimensionality reduction and classification. [Masters Thesis]. Colorado State University; 2016. Available from: http://hdl.handle.net/10217/176735

Colorado State University

16. Futia, Gregory Louis. Spatial frequency modulated single detector imaging.

Degree: MS(M.S.), Electrical and Computer Engineering, 2011, Colorado State University

URL: http://hdl.handle.net/10217/47273

► This thesis presents images of absorbing and fluorescent objects captured by modulating a time varying spatial frequency to an illumination beam. The modulator produces a… (more)

Subjects/Keywords: spatial frequency; imaging; single detector

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APA (6^th Edition):

Futia, G. L. (2011). Spatial frequency modulated single detector imaging. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/47273

Chicago Manual of Style (16^th Edition):

Futia, Gregory Louis. “Spatial frequency modulated single detector imaging.” 2011. Masters Thesis, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/47273.

MLA Handbook (7^th Edition):

Futia, Gregory Louis. “Spatial frequency modulated single detector imaging.” 2011. Web. 17 Jan 2021.

Vancouver:

Futia GL. Spatial frequency modulated single detector imaging. [Internet] [Masters thesis]. Colorado State University; 2011. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/47273.

Council of Science Editors:

Futia GL. Spatial frequency modulated single detector imaging. [Masters Thesis]. Colorado State University; 2011. Available from: http://hdl.handle.net/10217/47273

Colorado State University

17. Pakrooh, Pooria. Parameter estimation from compressed and sparse measurements.

Degree: PhD, Electrical and Computer Engineering, 2015, Colorado State University

URL: http://hdl.handle.net/10217/167122

► In this dissertation, the problem of parameter estimation from compressed and sparse noisy measurements is studied. First, fundamental estimation limits of the problem are analyzed.… (more)

▼ In this dissertation, the problem of parameter estimation from compressed and sparse noisy measurements is studied. First, fundamental estimation limits of the problem are analyzed. For that purpose, the effect of compressed sensing with random matrices on Fisher information, the Cramer-Rao Bound (CRB) and the Kullback-Leibler divergence are considered. The unknown parameters for the measurements are in the mean value function of a multivariate normal distribution. The class of random compression matrices considered in this work are those whose distribution is right-unitary invariant. The compression matrix whose elements are i.i.d. standard normal random variables is one such matrix. We show that for all such compression matrices, the Fisher information matrix has a complex matrix beta distribution. We also derive the distribution of CRB. These distributions can be used to quantify the loss in CRB as a function of the Fisher information of the non-compressed data. In our numerical examples, we consider a direction of arrival estimation problem and discuss the use of these distributions as guidelines for deciding whether compression should be considered, based on the resulting loss in performance. Then, the effect of compression on performance breakdown regions of parameter estimation methods is studied. Performance breakdown may happen when either the sample size or signal-to-noise ratio (SNR) falls below a certain threshold. The main reason for this threshold effect is that in low SNR or sample size regimes, many high resolution parameter estimation methods, including subspace methods as well as maximum likelihood estimation lose their capability to resolve signal and noise subspaces. This leads to a large error in parameter estimation. This phenomenon is called a subspace swap. The probability of a subspace swap for parameter estimation from compressed data is studied. A lower bound has been derived on the probability of a subspace swap in parameter estimation from compressed noisy data. This lower bound can be used as a tool to predict breakdown for different compression schemes at different SNRs. In the last part of this work, we look at the problem of parameter estimation for p damped complex exponentials, from the observation of their weighted and damped sum. This problem arises in spectrum estimation, vibration analysis, speech processing, system identification, and direction of arrival estimation. Our results differ from standard results of modal analysis to the extent that we consider sparse and co-prime samplings in space, or equivalently sparse and co-prime samplings in time. Our main result is a characterization of the orthogonal subspace. This is the subspace that is orthogonal to the signal subspace spanned by the columns of the generalized Vandermonde matrix of modes in sparse or coprime arrays. This characterization is derived in a form that allows us to adapt modern methods of linear prediction and approximate least squares for estimating mode parameters. Several numerical examples are presented… Advisors/Committee Members: Pezeshki, Ali (advisor), Scharf, Louis L. (advisor), Chong, Edwin K. P. (committee member), Luo, J. Rockey (committee member), Peterson, Chris (committee member).

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APA (6^th Edition):

Pakrooh, P. (2015). Parameter estimation from compressed and sparse measurements. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/167122

Chicago Manual of Style (16^th Edition):

Pakrooh, Pooria. “Parameter estimation from compressed and sparse measurements.” 2015. Doctoral Dissertation, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/167122.

MLA Handbook (7^th Edition):

Pakrooh, Pooria. “Parameter estimation from compressed and sparse measurements.” 2015. Web. 17 Jan 2021.

Vancouver:

Pakrooh P. Parameter estimation from compressed and sparse measurements. [Internet] [Doctoral dissertation]. Colorado State University; 2015. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/167122.

Council of Science Editors:

Pakrooh P. Parameter estimation from compressed and sparse measurements. [Doctoral Dissertation]. Colorado State University; 2015. Available from: http://hdl.handle.net/10217/167122

Colorado State University

18. Klausner, Nicholas Harold. Detection of multiple correlated time series and its application in synthetic aperture sonar imagery.

Degree: PhD, Electrical and Computer Engineering, 2014, Colorado State University

URL: http://hdl.handle.net/10217/83747

► Detecting the presence of a common but unknown signal among two or more data channels is a problem that finds its uses in many applications,… (more)

▼ Detecting the presence of a common but unknown signal among two or more data channels is a problem that finds its uses in many applications, including collaborative sensor networks, geological monitoring of seismic activity, radar, and sonar. Some detection systems in such situations use decision fusion to combine individual detection decisions into one global decision. However, this detection paradigm can be sub-optimal as local decisions are based on the perspective of a single sensory system. Thus, methods that capture the coherent or mutual information among multiple data sets are needed. This work considers the problem of testing for the independence among multiple (≥ 2) random vectors. The solution is attained by considering a Generalized Likelihood Ratio Test (GLRT) that tests the null hypothesis that the composite covariance matrix of the channels, a matrix containing all inter and intra-channel second-order information, is block-diagonal. The test statistic becomes a generalized Hadamard ratio given by the ratio of the determinant of the estimate of this composite covariance matrix over the product of the determinant of its diagonal blocks. One important question in the practical application of any likelihood ratio test is the values of the test statistic needed to achieve sufficient evidence in support of the decision to reject the null hypothesis. To gain some understanding of the false alarm probability or size of the test for the generalized Hadamard ratio, we employ the theory of Gram determinants to show that the likelihood ratio can be written as a product of ratios of the squared residual from two linear prediction problems. This expression for the likelihood ratio leads quite simply to the fact that the generalized Hadamard ratio is stochastically equivalent to a product of independently distributed beta random variables under the null hypothesis. Asymptotically, the scaled logarithm of the generalized Hadamard ratio converges in distribution to a chi-squared random variable as the number of samples used to estimate the composite covariance matrix grows large. The degrees of freedom for this chi-squared distribution are closely related to the dimensions of the parameter spaces considered in the development of the GLRT. Studies of this asymptotic distribution seem to indicate, however, that the rate of convergence is particularly slow for all but the simplest of problems and may therefore lack practicality. For this reason, we consider the use of saddlepoint approximations as a practical alternative for this problem. This leads to methods that can be used to determine the threshold needed to approximately achieve a desired false alarm probability. We next turn our attention to an alternative implementation of the generalized Hadamard ratio for 2-dimensional wide-sense stationary random processes. Although the true GLRT for this problem would impose a Toeplitz structure (more specifically, a Toeplitz-block-Toeplitz structure) on the estimate of the composite covariance matrix, an… Advisors/Committee Members: Azimi-Sadjadi, Mahmood R. (advisor), Scharf, Louis L. (advisor), Pezeshki, Ali (committee member), Cooley, Dan (committee member).

Subjects/Keywords: broadband coherence; generalized coherence; generalized likelihood ratio test; multichannel signal detection; synthetic aperture sonar

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APA (6^th Edition):

Klausner, N. H. (2014). Detection of multiple correlated time series and its application in synthetic aperture sonar imagery. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/83747

Chicago Manual of Style (16^th Edition):

Klausner, Nicholas Harold. “Detection of multiple correlated time series and its application in synthetic aperture sonar imagery.” 2014. Doctoral Dissertation, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/83747.

MLA Handbook (7^th Edition):

Klausner, Nicholas Harold. “Detection of multiple correlated time series and its application in synthetic aperture sonar imagery.” 2014. Web. 17 Jan 2021.

Vancouver:

Klausner NH. Detection of multiple correlated time series and its application in synthetic aperture sonar imagery. [Internet] [Doctoral dissertation]. Colorado State University; 2014. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/83747.

Council of Science Editors:

Klausner NH. Detection of multiple correlated time series and its application in synthetic aperture sonar imagery. [Doctoral Dissertation]. Colorado State University; 2014. Available from: http://hdl.handle.net/10217/83747

Colorado State University

19. Dinstel, Amanda. Wideband near-field array signal processing using the sparse representation framework.

Degree: MS(M.S.), Electrical and Computer Engineering, 2012, Colorado State University

URL: http://hdl.handle.net/10217/71633

► Recently, the field of sparse representation has attracted a great deal of attention from the perspective of target bearing (angle of arrival) estimation. This strategy… (more)

▼ Recently, the field of sparse representation has attracted a great deal of attention from the perspective of target bearing (angle of arrival) estimation. This strategy takes the approach that a target present in a sensor array's field of view may be treated as a sparse signal, e.g. if a discrete grid is defined over the search area, very few of the points in the grid will contain sources. Source localization then reduces to identifying the sparse grid point(s) which correspond to the highest concentration of energy. Tools from the sparse representation framework may be used to provide exceptionally high resolution solutions to this localization problem. In this work, existing sparse representation-based localization concepts are evaluated and extended for use in the specific application of detection and localization of wideband near-field targets in sonar data. While sparse representation offers a high-resolution detection and localization solution, the application of sparse representation-based techniques to the specific problem of sonar signal processing is challenging for several reasons. First, the general sparse representation-based angle of arrival problem formulation arises from a far-field array signal model, which allows source localization to be framed as a problem of identifying the unknown angle of arrival of sources in the search region. In contrast, the underwater targets under consideration in this work lie in the near-field which necessitates consideration of the unknown target range in addition to the unknown bearing angle. Second, a majority of current studies in the field of sparse representation-based source localization focus on narrowband signal processing. A handful of researchers have explored the extension of sparse recovery to the wideband problem, but most of these approaches require assumptions about the structure (i.e. sparsity profile) of the data, and these assumptions are not applicable to the sonar returns studied in this work. Further, sparse representation-based source localization methods suffer from many of the same limitations as traditional sonar processing techniques, such as sensitivity to the effects of sonar platform motion and other sources of measurement error. Such uncertainties may present themselves as perturbations in the observed data, mismatch of the defined search grid, or both, and ultimately serve to degrade the performance of sparse representation-based source localization algorithms. In this work, a near-field, wideband array signal processing method is developed which seeks to overcome these challenges inherent to sonar signal processing by expanding on existing concepts from the sparse representation framework. A comprehensive study was performed to evaluate the capabilities of the proposed sonar processing method for detection and localization of targets present in two sonar data sets, namely the Pond Experiment 2012 (PondEx10) data set, which was collected in a man-made pond facility using a rail-mounted sonar system, and the Davis Point data… Advisors/Committee Members: Azimi-Sadjadi, Mahmood R. (advisor), Chong, Edwin (committee member), Pezeshki, Ali (committee member), Breidt, Jay (committee member).

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APA (6^th Edition):

Dinstel, A. (2012). Wideband near-field array signal processing using the sparse representation framework. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/71633

Chicago Manual of Style (16^th Edition):

Dinstel, Amanda. “Wideband near-field array signal processing using the sparse representation framework.” 2012. Masters Thesis, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/71633.

MLA Handbook (7^th Edition):

Dinstel, Amanda. “Wideband near-field array signal processing using the sparse representation framework.” 2012. Web. 17 Jan 2021.

Vancouver:

Dinstel A. Wideband near-field array signal processing using the sparse representation framework. [Internet] [Masters thesis]. Colorado State University; 2012. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/71633.

Council of Science Editors:

Dinstel A. Wideband near-field array signal processing using the sparse representation framework. [Masters Thesis]. Colorado State University; 2012. Available from: http://hdl.handle.net/10217/71633

Colorado State University

20. Zhang, Yang. Continuum limits of Markov chains with application to wireless network modeling and control.

Degree: PhD, Electrical and Computer Engineering, 2014, Colorado State University

URL: http://hdl.handle.net/10217/82486

► We investigate the continuum limits of a class of Markov chains. The investigation of such limits is motivated by the desire to model networks with… (more)

Subjects/Keywords: partial differential equations; network modeling; modeling; Markov processes

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APA (6^th Edition):

Zhang, Y. (2014). Continuum limits of Markov chains with application to wireless network modeling and control. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/82486

Chicago Manual of Style (16^th Edition):

Zhang, Yang. “Continuum limits of Markov chains with application to wireless network modeling and control.” 2014. Doctoral Dissertation, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/82486.

MLA Handbook (7^th Edition):

Zhang, Yang. “Continuum limits of Markov chains with application to wireless network modeling and control.” 2014. Web. 17 Jan 2021.

Vancouver:

Zhang Y. Continuum limits of Markov chains with application to wireless network modeling and control. [Internet] [Doctoral dissertation]. Colorado State University; 2014. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/82486.

Council of Science Editors:

Zhang Y. Continuum limits of Markov chains with application to wireless network modeling and control. [Doctoral Dissertation]. Colorado State University; 2014. Available from: http://hdl.handle.net/10217/82486

Colorado State University

21. Zahedi, Ramin. Compressive measurement design for detection and estimation of sparse signals.

Degree: PhD, Electrical and Computer Engineering, 2013, Colorado State University

URL: http://hdl.handle.net/10217/80995

► We study the problem of designing compressive measurement matrices for two sets of problems. In the first set, we consider the problem of adaptively designing… (more)

▼ We study the problem of designing compressive measurement matrices for two sets of problems. In the first set, we consider the problem of adaptively designing compressive measurement matrices for estimating time-varying sparse signals. We formulate this problem as a Partially Observable Markov Decision Process (POMDP). This formulation allows us to use Bellman's principle of optimality in the implementation of multi-step lookahead designs of compressive measurements. We introduce two variations of the compressive measurement design problem. In the first variation, we consider the problem of selecting a prespecified number of measurement vectors from a predefined library as entries of the compressive measurement matrix at each time step. In the second variation, the number of compressive measurements, i.e., the number of rows of the measurement matrix, is adaptively chosen. Once the number of measurements is determined, the matrix entries are chosen according to a prespecified adaptive scheme. Each of these two problems is judged by a separate performance criterion. The gauge of efficiency in the first problem is the conditional mutual information between the sparse signal support and the measurements. The second problem applies a linear combination of the number of measurements and the conditional mutual information as the performance measure. We present several simulations in which the primary focus is the application of a method known as rollout. The significant computational load for using rollout has also inspired us to adapt two data association heuristics in our simulations to the compressive sensing paradigm. These heuristics show promising decreases in the amount of computation for propagating distributions and searching for optimal solutions. In the second set of problems, we consider the problem of testing for the presence (or detection) of an unknown static sparse signal in additive white noise. Given a fixed measurement budget, much smaller than the dimension of the signal, we consider the general problem of designing compressive measurements to maximize the measurement signal-to-noise ratio (SNR), as increasing SNR improves the detection performance in a large class of detectors. We use a lexicographic optimization approach, where the optimal measurement design for sparsity level k is sought only among the set of measurement matrices that satisfy the optimality conditions for sparsity level k-1. We consider optimizing two different SNR criteria, namely a worst-case SNR measure, over all possible realizations of a k-sparse signal, and an average SNR measure with respect to a uniform distribution on the locations of the up to k nonzero entries in the signal. We establish connections between these two criteria and certain classes of tight frames. We constrain our measurement matrices to the class of tight frames to avoid coloring the noise covariance matrix. For the worst-case problem, we show that the optimal measurement matrix is a Grassmannian line packing for most—and a uniform tight frame for… Advisors/Committee Members: Chong, Edwin K. P. (advisor), Pezeshki, Ali (advisor), Estep, Donald (committee member), Young, Peter M. (committee member).

Subjects/Keywords: compressed sensing; dynamic programming; partially observable Markov decision processes; Q-learning; sparse signal detection; sparse signal estimation

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APA (6^th Edition):

Zahedi, R. (2013). Compressive measurement design for detection and estimation of sparse signals. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/80995

Chicago Manual of Style (16^th Edition):

Zahedi, Ramin. “Compressive measurement design for detection and estimation of sparse signals.” 2013. Doctoral Dissertation, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/80995.

MLA Handbook (7^th Edition):

Zahedi, Ramin. “Compressive measurement design for detection and estimation of sparse signals.” 2013. Web. 17 Jan 2021.

Vancouver:

Zahedi R. Compressive measurement design for detection and estimation of sparse signals. [Internet] [Doctoral dissertation]. Colorado State University; 2013. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/80995.

Council of Science Editors:

Zahedi R. Compressive measurement design for detection and estimation of sparse signals. [Doctoral Dissertation]. Colorado State University; 2013. Available from: http://hdl.handle.net/10217/80995

Colorado State University

22. Krakow, Lucas W. Spanning sensor resource management.

Degree: PhD, Electrical and Computer Engineering, 2018, Colorado State University

URL: http://hdl.handle.net/10217/193188

► This paper presents multiple applications of sensor resource management. The general focus entails two chapters on adaptive estimation of time-varying sparse signals and three chapters… (more)

Subjects/Keywords: decision control; Q-value approximations; unmanned aerial vehicles; partially observable Markov decision process; autonomous control; sparse signal recovery

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APA (6^th Edition):

Krakow, L. W. (2018). Spanning sensor resource management. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/193188

Chicago Manual of Style (16^th Edition):

Krakow, Lucas W. “Spanning sensor resource management.” 2018. Doctoral Dissertation, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/193188.

MLA Handbook (7^th Edition):

Krakow, Lucas W. “Spanning sensor resource management.” 2018. Web. 17 Jan 2021.

Vancouver:

Krakow LW. Spanning sensor resource management. [Internet] [Doctoral dissertation]. Colorado State University; 2018. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/193188.

Council of Science Editors:

Krakow LW. Spanning sensor resource management. [Doctoral Dissertation]. Colorado State University; 2018. Available from: http://hdl.handle.net/10217/193188

23. Mosharraf Ghahfarokhi, Negar. Cooperative defense mechanisms for detection, identification and filtering of DDoS attacks.

Degree: PhD, Electrical and Computer Engineering, 2016, Colorado State University

URL: http://hdl.handle.net/10217/176690

To view the abstract, please see the full text of the document. Advisors/Committee Members: Jayasumana, Anura P. (advisor), Ray, Indrakshi (advisor), Pezeshki, Ali (committee member), Malaiya, Yashwant (committee member).

…40 3.4.3 Colorado State University Dataset… …traffic against DDoS attacks by analysis of network traffic collected from Colorado State… …State University [20] and University of Auckland dataset [6]. The… …University, Auckland University, and attack traffic from CAIDA. It is important to minimize the… …evaluated using the DARPA 1998 dataset [19] as well as extensive analysis over Colorado…

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APA (6^th Edition):

Mosharraf Ghahfarokhi, N. (2016). Cooperative defense mechanisms for detection, identification and filtering of DDoS attacks. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/176690

Chicago Manual of Style (16^th Edition):

Mosharraf Ghahfarokhi, Negar. “Cooperative defense mechanisms for detection, identification and filtering of DDoS attacks.” 2016. Doctoral Dissertation, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/176690.

MLA Handbook (7^th Edition):

Mosharraf Ghahfarokhi, Negar. “Cooperative defense mechanisms for detection, identification and filtering of DDoS attacks.” 2016. Web. 17 Jan 2021.

Vancouver:

Mosharraf Ghahfarokhi N. Cooperative defense mechanisms for detection, identification and filtering of DDoS attacks. [Internet] [Doctoral dissertation]. Colorado State University; 2016. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/176690.

Council of Science Editors:

Mosharraf Ghahfarokhi N. Cooperative defense mechanisms for detection, identification and filtering of DDoS attacks. [Doctoral Dissertation]. Colorado State University; 2016. Available from: http://hdl.handle.net/10217/176690

24. Bhatnagar, Sakshi. Performance assessment of multi-walled carbon nanotube interconnects using advanced polynomial chaos schemes.

Degree: MS(M.S.), Electrical and Computer Engineering, 2019, Colorado State University

URL: http://hdl.handle.net/10217/195363

► With the continuous miniaturization in the latest VLSI technologies, manufacturing uncertainties at nanoscale processes and operations are unpredictable at the chip level, packaging level and… (more)

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APA (6^th Edition):

Bhatnagar, S. (2019). Performance assessment of multi-walled carbon nanotube interconnects using advanced polynomial chaos schemes. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/195363

Chicago Manual of Style (16^th Edition):

Bhatnagar, Sakshi. “Performance assessment of multi-walled carbon nanotube interconnects using advanced polynomial chaos schemes.” 2019. Masters Thesis, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/195363.

MLA Handbook (7^th Edition):

Bhatnagar, Sakshi. “Performance assessment of multi-walled carbon nanotube interconnects using advanced polynomial chaos schemes.” 2019. Web. 17 Jan 2021.

Vancouver:

Bhatnagar S. Performance assessment of multi-walled carbon nanotube interconnects using advanced polynomial chaos schemes. [Internet] [Masters thesis]. Colorado State University; 2019. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/195363.

Council of Science Editors:

Bhatnagar S. Performance assessment of multi-walled carbon nanotube interconnects using advanced polynomial chaos schemes. [Masters Thesis]. Colorado State University; 2019. Available from: http://hdl.handle.net/10217/195363

25. Tang, Yanru. Distributed wireless networking with an enhanced physical-link layer interface.

Degree: PhD, Electrical and Computer Engineering, 2019, Colorado State University

URL: http://hdl.handle.net/10217/195248

► This thesis focuses on the cross-layer design of physical and data link layers to support efficient distributed wireless networking. At the physical layer, distributed coding… (more)

▼ This thesis focuses on the cross-layer design of physical and data link layers to support efficient distributed wireless networking. At the physical layer, distributed coding theorems are proposed to prepare each transmitter with an ensemble of channel codes. In a time slot, a transmitter chooses a code to encode its messages and such a choice is not shared with other transmitters or with the receiver. The receiver guarantees either reliable message decoding or reliable collision report depending on whether a predetermined reliability threshold can be met. Under the assumption that the codeword length can be taken to infinity, the distributed capacity of a discrete-time memoryless multiple access channel is derived and is shown to coincide with the classical Shannon capacity region of the same channel. An achievable error performance bound is also presented for the case when codeword length is finite. With the new coding theorems, link layer users can be equipped with multiple transmission options corresponding to the physical layer code ensemble. This enables link layer users to exploit advanced wireless capabilities such as rate and power adaptation, which is not supported in the current network architecture. To gain understandings on how link layer users should efficiently exploit these new capabilities, the corresponding link layer problem is investigated from two different perspectives. Under the assumption that each user is provided with multiple transmission options, the link layer problem is first formulated using a game theoretic model where each user adapts its transmission scheme to maximize a utility function. The condition under which the medium access control game has a unique Nash equilibrium is obtained. Simulation results show that, when multiple transmission options are provided, users in a distributed network tend to converge to channel sharing schemes that are consistent with the well-known information theoretic understandings. A stochastic approximation framework is adopted to further study the link layer problem for the case when each user has a single transmission option as well as the case when each user has multiple transmission options. Assume that each user is backlogged with a saturated message queue. With a generally-modeled channel, a distributed medium access control framework is proposed to adapt the transmission scheme of each user to maximize an arbitrarily chosen symmetric network utility. The proposed framework suggests that the receiver should measure the success probability of a carefully designed virtual packet or a set of virtual packets, and feed such information back to the transmitters. Given channel feedback from the receiver, each transmitter should obtain a user number estimate by comparing the measured success probability with the corresponding theoretical value, and then adapt its transmission scheme accordingly. Conditions under which the proposed algorithm should converge to a designed unique equilibrium are characterized. Simulation results are provided to… Advisors/Committee Members: Luo, Rockey (advisor), Yang, Liuqing (committee member), Pezeshki, Ali (committee member), Wang, Haonan (committee member).

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APA (6^th Edition):

Tang, Y. (2019). Distributed wireless networking with an enhanced physical-link layer interface. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/195248

Chicago Manual of Style (16^th Edition):

Tang, Yanru. “Distributed wireless networking with an enhanced physical-link layer interface.” 2019. Doctoral Dissertation, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/195248.

MLA Handbook (7^th Edition):

Tang, Yanru. “Distributed wireless networking with an enhanced physical-link layer interface.” 2019. Web. 17 Jan 2021.

Vancouver:

Tang Y. Distributed wireless networking with an enhanced physical-link layer interface. [Internet] [Doctoral dissertation]. Colorado State University; 2019. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/195248.

Council of Science Editors:

Tang Y. Distributed wireless networking with an enhanced physical-link layer interface. [Doctoral Dissertation]. Colorado State University; 2019. Available from: http://hdl.handle.net/10217/195248

26. Hicks, Adam. Utilization of convolutional neural networks in the classification of snowflakes based on images by a multi-angle snowflake camera.

Degree: MS(M.S.), Electrical and Computer Engineering, 2019, Colorado State University

URL: http://hdl.handle.net/10217/197252

► Recent developments in machine learning are applied to in-situ data collected by a Multi-Angle Snowflake Camera (MASC), incorporating convolutional and residual networks in big data… (more)

Subjects/Keywords: machine learning; in-situ measurement

…common focal center distances of 10 cm. The system used at Colorado State University, Figure 2… …Colorado State University, Fort Collins. Feb. 2nd – April 30th 2018. 24. Murphy, K. P… …State University. The network architecture is the ResNet-50, which was chosen over AlexNet… …implemented using Matlab™ 2018b, with the Deep Learning and Machine Learning Toolboxes at Colorado…

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APA (6^th Edition):

Hicks, A. (2019). Utilization of convolutional neural networks in the classification of snowflakes based on images by a multi-angle snowflake camera. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/197252

Chicago Manual of Style (16^th Edition):

Hicks, Adam. “Utilization of convolutional neural networks in the classification of snowflakes based on images by a multi-angle snowflake camera.” 2019. Masters Thesis, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/197252.

MLA Handbook (7^th Edition):

Hicks, Adam. “Utilization of convolutional neural networks in the classification of snowflakes based on images by a multi-angle snowflake camera.” 2019. Web. 17 Jan 2021.

Vancouver:

Hicks A. Utilization of convolutional neural networks in the classification of snowflakes based on images by a multi-angle snowflake camera. [Internet] [Masters thesis]. Colorado State University; 2019. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/197252.

Council of Science Editors:

Hicks A. Utilization of convolutional neural networks in the classification of snowflakes based on images by a multi-angle snowflake camera. [Masters Thesis]. Colorado State University; 2019. Available from: http://hdl.handle.net/10217/197252

27. Chatterjee, Shibayan. Multi-attribute query resolution in structured peer-to-peer networks.

Degree: MS(M.S.), Electrical and Computer Engineering, 2016, Colorado State University

URL: http://hdl.handle.net/10217/178845

► Collaborative grid and cloud computing applications may be implemented by forming virtual clusters on demand. Formation of such clusters will require diverse resources with specific… (more)

▼ Collaborative grid and cloud computing applications may be implemented by forming virtual clusters on demand. Formation of such clusters will require diverse resources with specific attributes to execute and support the specific application and its performance requirements. This thesis focuses on formation of such systems by looking up resources over a distributed peer-to-peer system. Discovery of appropriate resources from an enormous distributed pool of resources becomes tedious, but it should be resolved with minimum cost and latency. There can be a number of attributes characterizing each resource, and these attributes may have ranges of values depending upon the characteristics of the resources. Thus, when performing a look-up for appropriate resources with a peer-to-peer approach, the objective moves from a single-dimensional look-up problem to a multi-dimensional look-up problem. The look-up operation has to be optimized in terms of delay in resolution, hop-count, communication cost, and overhead cost. This thesis develops and evaluates an architecture aimed at resolving this n-dimensional peer-to-peer look-up problem. The optimality of the proposed solution is evaluated in terms of communication overhead, delay, and hop count for look up. The complexity of n-dimensional look-up problem is further reduced in terms of dimensionality by utilizing the correlation between different attribute characteristics. The proposed architecture uses a structured peer-to-peer network in the form of multiple rings, grouped together on the basis of individual attributes thus forming a Ring of Rings (ROR). Chord protocol is used to maintain the scalability and for having communication cost for lookup within logarithmic time complexity. Communication within the network is done using Bloom filters as a data structure, which represents the resources satisfying different attribute values. The novelty of the architecture and the communication methodology lies in the fact that architecture facilitates any number of attributes having any range of values. Furthermore, use of Bloom-filters for communication reduces the overhead normally required to carry around long lists of resources to perform the final intersection that resolves the query. Using Bloom-filters greatly reduces the communication overhead and the cost of communication. The ROR architecture coupled with Bloom-filter messages reduces the message sizes considerably, but it introduces a certain amount of false positives. The findings indicate that with the optimum number of hash-functions and the optimum sized Bloom-filter, a ROR peer-to-peer architecture to search for multi-attribute queries can be much more efficient than the conventional systems used for the resolution of same type of queries. Queries associated with many systems request attributes which are correlated to each other. The research also addresses the identification of such resources more efficiently based on correlation of the attributes. The ROR architecture can be tuned for resolving these kinds of… Advisors/Committee Members: Jayasumana, Anura (advisor), Pezeshki, Ali (committee member), Pallickara, Sangmi Lee (committee member).

Subjects/Keywords: caching; overlapped rings; range queries; multi-attribute resources; bloom-filters; peer-to-peer networks (P2P)

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APA (6^th Edition):

Chatterjee, S. (2016). Multi-attribute query resolution in structured peer-to-peer networks. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/178845

Chicago Manual of Style (16^th Edition):

Chatterjee, Shibayan. “Multi-attribute query resolution in structured peer-to-peer networks.” 2016. Masters Thesis, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/178845.

MLA Handbook (7^th Edition):

Chatterjee, Shibayan. “Multi-attribute query resolution in structured peer-to-peer networks.” 2016. Web. 17 Jan 2021.

Vancouver:

Chatterjee S. Multi-attribute query resolution in structured peer-to-peer networks. [Internet] [Masters thesis]. Colorado State University; 2016. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/178845.

Council of Science Editors:

Chatterjee S. Multi-attribute query resolution in structured peer-to-peer networks. [Masters Thesis]. Colorado State University; 2016. Available from: http://hdl.handle.net/10217/178845

28. Krishna Prasad, Aditi. Accurate dimension reduction based polynomial chaos approach for uncertainty quantification of high speed networks.

Degree: PhD, Electrical and Computer Engineering, 2018, Colorado State University

URL: http://hdl.handle.net/10217/189391

► With the continued miniaturization of VLSI technology to sub-45 nm levels, uncertainty in nanoscale manufacturing processes and operating conditions have been found to translate into… (more)

▼ With the continued miniaturization of VLSI technology to sub-45 nm levels, uncertainty in nanoscale manufacturing processes and operating conditions have been found to translate into unpredictable system-level behavior of integrated circuits. As a result, there is a need for contemporary circuit simulation tools/solvers to model the forward propagation of device level uncertainty to the network response. Recently, techniques based on the robust generalized polynomial chaos (PC) theory have been reported for the uncertainty quantification of high-speed circuit, electromagnetic, and electronic packaging problems. The major bottleneck in all PC approaches is that the computational effort required to generate the metamodel scales in a polynomial fashion with the number of random input dimensions. In order to mitigate this poor scalability of conventional PC approaches, in this dissertation, a reduced dimensional PC approach is proposed. This PC approach is based on using a high dimensional model representation (HDMR) to quantify the relative impact of each dimension on the variance of the network response. The reduced dimensional PC approach is further extended to problems with mixed aleatory and epistemic uncertainties. In this mixed PC approach, a parameterized formulation of analysis of variance (ANOVA) is used to identify the statistically significant dimensions and subsequently perform dimension reduction. Mixed problems are however characterized by far greater number of dimensions than purely epistemic or aleatory problems, thus exacerbating the poor scalability of PC expansions. To address this issue, in this dissertation, a novel dimension fusion approach is proposed. This approach fuses the epistemic and aleatory dimensions within the same model parameter into a mixed dimension. The accuracy and efficiency of the proposed approaches are validated through multiple numerical examples. Advisors/Committee Members: Roy, Sourajeey (advisor), Pezeshki, Ali (committee member), Notaros, Branislav (committee member), Anderson, Charles (committee member).

Subjects/Keywords: dimension fusion; polynomial chaos; uncertainty quantification; epistemic; aleatory; sensitivity indices

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APA (6^th Edition):

Krishna Prasad, A. (2018). Accurate dimension reduction based polynomial chaos approach for uncertainty quantification of high speed networks. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/189391

Chicago Manual of Style (16^th Edition):

Krishna Prasad, Aditi. “Accurate dimension reduction based polynomial chaos approach for uncertainty quantification of high speed networks.” 2018. Doctoral Dissertation, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/189391.

MLA Handbook (7^th Edition):

Krishna Prasad, Aditi. “Accurate dimension reduction based polynomial chaos approach for uncertainty quantification of high speed networks.” 2018. Web. 17 Jan 2021.

Vancouver:

Krishna Prasad A. Accurate dimension reduction based polynomial chaos approach for uncertainty quantification of high speed networks. [Internet] [Doctoral dissertation]. Colorado State University; 2018. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/189391.

Council of Science Editors:

Krishna Prasad A. Accurate dimension reduction based polynomial chaos approach for uncertainty quantification of high speed networks. [Doctoral Dissertation]. Colorado State University; 2018. Available from: http://hdl.handle.net/10217/189391

29. Hosseini, Somayeh. Sparse representations in multi-kernel dictionaries for in-situ classification of underwater objects.

Degree: MS(M.S.), Electrical and Computer Engineering, 2017, Colorado State University

URL: http://hdl.handle.net/10217/181340

► The performance of the kernel-based pattern classification algorithms depends highly on the selection of the kernel function and its parameters. Consequently in the recent years… (more)

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APA (6^th Edition):

Hosseini, S. (2017). Sparse representations in multi-kernel dictionaries for in-situ classification of underwater objects. (Masters Thesis). Colorado State University. Retrieved from http://hdl.handle.net/10217/181340

Chicago Manual of Style (16^th Edition):

Hosseini, Somayeh. “Sparse representations in multi-kernel dictionaries for in-situ classification of underwater objects.” 2017. Masters Thesis, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/181340.

MLA Handbook (7^th Edition):

Hosseini, Somayeh. “Sparse representations in multi-kernel dictionaries for in-situ classification of underwater objects.” 2017. Web. 17 Jan 2021.

Vancouver:

Hosseini S. Sparse representations in multi-kernel dictionaries for in-situ classification of underwater objects. [Internet] [Masters thesis]. Colorado State University; 2017. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/181340.

Council of Science Editors:

Hosseini S. Sparse representations in multi-kernel dictionaries for in-situ classification of underwater objects. [Masters Thesis]. Colorado State University; 2017. Available from: http://hdl.handle.net/10217/181340

30. Liu, Yajing. Performance bounds for greedy strategies in submodular optimization problems.

Degree: PhD, Electrical and Computer Engineering, 2018, Colorado State University

URL: http://hdl.handle.net/10217/191438

To view the abstract, please see the full text of the document. Advisors/Committee Members: Chong, Edwin K. P. (advisor), Pezeshki, Ali (advisor), Luo, J. Rockey (committee member), Bates, Dan (committee member).

Subjects/Keywords: curvature; matroid; submodular; greedy; approximate dynamic programming; polymatroid

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APA (6^th Edition):

Liu, Y. (2018). Performance bounds for greedy strategies in submodular optimization problems. (Doctoral Dissertation). Colorado State University. Retrieved from http://hdl.handle.net/10217/191438

Chicago Manual of Style (16^th Edition):

Liu, Yajing. “Performance bounds for greedy strategies in submodular optimization problems.” 2018. Doctoral Dissertation, Colorado State University. Accessed January 17, 2021. http://hdl.handle.net/10217/191438.

MLA Handbook (7^th Edition):

Liu, Yajing. “Performance bounds for greedy strategies in submodular optimization problems.” 2018. Web. 17 Jan 2021.

Vancouver:

Liu Y. Performance bounds for greedy strategies in submodular optimization problems. [Internet] [Doctoral dissertation]. Colorado State University; 2018. [cited 2021 Jan 17]. Available from: http://hdl.handle.net/10217/191438.

Council of Science Editors:

Liu Y. Performance bounds for greedy strategies in submodular optimization problems. [Doctoral Dissertation]. Colorado State University; 2018. Available from: http://hdl.handle.net/10217/191438

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