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Rutgers University
1.
Almansouri, Saif.
Reduced-order Kalman filter for a class of continuous - time systems with slow and fast modes.
Degree: MS, Electrical and Computer Engineering, 2016, Rutgers University
URL: https://rucore.libraries.rutgers.edu/rutgers-lib/51186/ 
► In this thesis, complete decomposition of the Kalman filter into the reduced-order Kalman filter with slow and fast modes is addressed. First, we investigate the…
(more)
▼ In this thesis, complete decomposition of the Kalman filter into the reduced-order Kalman filter with slow and fast modes is addressed. First, we investigate the decomposition so that the slow and fast filters are completely separated with both of filters driven by the system measurements. The simulation results are presented for such a decomposition using an aircraft example. In the second part, this thesis presents the design of reduced order Kalman filters for systems with both slow and fast modes for the case of perfect measurement. The main advantage of the reduced order approach is moderating and reducing mathematical difficulties to obtain the optimal state estimation. This will facilitate the use of Kalman filter for a class of real-time physical systems. In this thesis, we explain the effectiveness of the proposed design through theoretical studies and simulation results.
Advisors/Committee Members: Gajic, Zoran (chair), Godrich, Hana (internal member), Orfanidis, Sophocles (internal member).
Subjects/Keywords: Kalman filtering
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APA (6th Edition):
Almansouri, S. (2016). Reduced-order Kalman filter for a class of continuous - time systems with slow and fast modes. (Masters Thesis). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/51186/
Chicago Manual of Style (16th Edition):
Almansouri, Saif. “Reduced-order Kalman filter for a class of continuous - time systems with slow and fast modes.” 2016. Masters Thesis, Rutgers University. Accessed January 20, 2021.
https://rucore.libraries.rutgers.edu/rutgers-lib/51186/.
MLA Handbook (7th Edition):
Almansouri, Saif. “Reduced-order Kalman filter for a class of continuous - time systems with slow and fast modes.” 2016. Web. 20 Jan 2021.
Vancouver:
Almansouri S. Reduced-order Kalman filter for a class of continuous - time systems with slow and fast modes. [Internet] [Masters thesis]. Rutgers University; 2016. [cited 2021 Jan 20].
Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/51186/.
Council of Science Editors:
Almansouri S. Reduced-order Kalman filter for a class of continuous - time systems with slow and fast modes. [Masters Thesis]. Rutgers University; 2016. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/51186/
Rutgers University
2.
Škatarić, Maja, 1986-.
Fold change detection in 3-node enzymatic networks.
Degree: MS, Electrical and Computer Engineering, 2011, Rutgers University
URL: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000061515
► Complex networks are studied across many fields of science. To discover design principles that underlie these networks, network motifs are introduced, as sub-graphs of interconnections…
(more)
▼ Complex networks are studied across many fields of science. To discover design principles that underlie these networks, network motifs are introduced, as sub-graphs of interconnections occurring in complex networks much more often than expected at random. A distinct set of network motifs were identified in many types of biological networks, such as gene transcriptional networks, neuronal networks, and enzymatic networks, but only small fraction of them have been well described. By connecting recurrent motifs with a particular cellular function, it is hoped that one can understand the dynamics of the entire network based on the dynamics of its core motifs. Two biologically important functions were introduced and motivated through examples from biology, namely, exact adaptation, which represents a system's ability to respond to a change in the input signal and return to its pre-stimulated state even when the change in input persists, and Fold Change Detection, which is a special property of adapting systems, where the output is invariant under the scaling of inputs. In this thesis, the study of network motifs was used as a motivation to further explore the dynamics of all 3-node enzymatic networks capable of achieving Fold Change Detection property. A search through 16,038 topologies sampled with 10,000 parameters each, led to the conclusion that despite the diversity of enzymatic circuits, only small number of them is capable of achieving the FCD property, and the mechanism for achieving it can be understood through a theoretical and computational analysis.
Advisors/Committee Members: Sontag, Eduardo (chair), Orfanidis, Sophocles (internal member), Spasojevic, Predrag (internal member).
Subjects/Keywords: Multienzyme complexes
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APA (6th Edition):
Škatarić, Maja, 1. (2011). Fold change detection in 3-node enzymatic networks. (Masters Thesis). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000061515
Chicago Manual of Style (16th Edition):
Škatarić, Maja, 1986-. “Fold change detection in 3-node enzymatic networks.” 2011. Masters Thesis, Rutgers University. Accessed January 20, 2021.
http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000061515.
MLA Handbook (7th Edition):
Škatarić, Maja, 1986-. “Fold change detection in 3-node enzymatic networks.” 2011. Web. 20 Jan 2021.
Vancouver:
Škatarić, Maja 1. Fold change detection in 3-node enzymatic networks. [Internet] [Masters thesis]. Rutgers University; 2011. [cited 2021 Jan 20].
Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000061515.
Council of Science Editors:
Škatarić, Maja 1. Fold change detection in 3-node enzymatic networks. [Masters Thesis]. Rutgers University; 2011. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000061515
Rutgers University
3.
Sridhar Dharmarajan, Karthik, 1991-.
Estimation and adaptive equalization of communications channels.
Degree: MS, Electrical and Computer Engineering, 2015, Rutgers University
URL: https://rucore.libraries.rutgers.edu/rutgers-lib/46440/
► The focus of this research is to determine the channel impulse response of a communications link and then equalize the channel to mitigate the e…
(more)
▼ The focus of this research is to determine the channel impulse response of a communications link and then equalize the channel to mitigate the e ffects of fading on the received signal. Traditionally, channel identifi cation is achieved using a deconvolution process implemented in the time-domain. An alternative method is to perform deconvolution, for the purpose of estimating communications channel structures, in the wavelet transform domain. This approach is attractive for use in agile transceivers that utilize the wavelet domain for functions such as automatic modulation recognition. An equivalent method for deconvolving discrete time-domain signals within the Discrete Wavelet Transform (DWT) framework is explained. This method of deconvolution can be applied at any level of DWT resolution from which the complete channel impulse response can be estimated. Computer simulations have been conducted to characterize the performance of the channel estimation algorithm using the Mean Square Error (MSE) criterion. The simulation experiments are performed for two di fferent channel models characterized by a Power Delay Profi le (PDP), i.e., the Gaussian PDP and the Exponential PDP. Channel conditions of slow and fast fading are considered. In addition, the faded channel output signals are corrupted by AWGN having ratios of bit energy-to-noise spectral density, Eb/N0, in the range from 0 to 30 dB. It has been found that, for both channel models, the best channel impulse response estimate is obtained from the DWT detail coe fficients at the 1st level of resolution resulting in computational effi ciency. A novel method, based on the classic LMS algorithm, has been developed for adaptive equalization of channels in the wavelet domain. Computer simulation experiments for channel equalization show that the DWT-LMS algorithm, using a Haar wavelet, performs better than the LMS algorithm for the Gaussian PDP channel in terms of the achievable bit error probabilities.
Advisors/Committee Members: Daut, David G (chair), Orfanidis, Sophocles (internal member), Gajic, Zoran (internal member).
Subjects/Keywords: Wavelets (Mathematics); Transformations (Mathematics)
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APA (6th Edition):
Sridhar Dharmarajan, Karthik, 1. (2015). Estimation and adaptive equalization of communications channels. (Masters Thesis). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/46440/
Chicago Manual of Style (16th Edition):
Sridhar Dharmarajan, Karthik, 1991-. “Estimation and adaptive equalization of communications channels.” 2015. Masters Thesis, Rutgers University. Accessed January 20, 2021.
https://rucore.libraries.rutgers.edu/rutgers-lib/46440/.
MLA Handbook (7th Edition):
Sridhar Dharmarajan, Karthik, 1991-. “Estimation and adaptive equalization of communications channels.” 2015. Web. 20 Jan 2021.
Vancouver:
Sridhar Dharmarajan, Karthik 1. Estimation and adaptive equalization of communications channels. [Internet] [Masters thesis]. Rutgers University; 2015. [cited 2021 Jan 20].
Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/46440/.
Council of Science Editors:
Sridhar Dharmarajan, Karthik 1. Estimation and adaptive equalization of communications channels. [Masters Thesis]. Rutgers University; 2015. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/46440/
Rutgers University
4.
Sagar, Nishant, 1986-.
Powerline communications systems: overview and analysis.
Degree: MS, Electrical and Computer Engineering, 2011, Rutgers University
URL: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000061509
► The electric power distribution grid is a medium over which fast and reliable communication services can be provided. Power Line Communications (PLC) systems provide an…
(more)
▼ The electric power distribution grid is a medium over which fast and reliable communication services can be provided. Power Line Communications (PLC) systems provide an alternative to wireless communications in the transmission of data within buildings and vehicles. In recent years, increased interest in PLC systems for both commercial and residence applications has resulted in the development of standards for use of the electric power grid as a communications channel conveying messages in addition to power. The types of applications range from simple inexpensive services centered around networked household appliances, where data rates are on the order of kilobits per second, to Internet access via the electrical outlet wall socket, where data rates are on the order of megabits per second. Currently, PLC systems can accommodate high- iii speed networking that includes broadband Internet access, voice over-IP, and the interconnectivity of home entertainment devices. The development of a Power Line Communications system presents a significant challenge for the communications engineer due to the unusual channel characteristics that affect high-speed signal transmission. The electric power grid is designed for, and operated at, 50/60 Hz throughout the world. Furthermore, the topology of a local electric power grid network is often very irregular resulting in significant dispersion of the transmitted message signals. This thesis presents an overview of the major features and characteristics of PLC systems, the fundamental properties of powerline channels, and an analysis of PLC system performance in the presence of realistic powerline channel conditions. The development of a powerline communication system requires detailed knowledge of the electric power grid channel properties, such as the frequency transfer function and the interference processes, in order to choose a suitable transmission method. The noise interference and channel multipath effects are the main impairments to the performance of PLC systems. This thesis presents appropriate channel models for use in the design of PLC systems. In particular, the Bit Error Rate (BER) performance of a single-carrier Binary Phase Shift Keying (BPSK) system operating over a multipath channel is analyzed and compared with the performance obtained with a multi-carrier data transmission scheme.
Advisors/Committee Members: Sagar, Nishant, 1986- (author), Daut, David G (chair), Orfanidis, Sophocles (internal member), Sannuti, Pedda (internal member).
Subjects/Keywords: Electric power systems—Communication systems; Electric power systems – Standards
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APA (6th Edition):
Sagar, Nishant, 1. (2011). Powerline communications systems: overview and analysis. (Masters Thesis). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000061509
Chicago Manual of Style (16th Edition):
Sagar, Nishant, 1986-. “Powerline communications systems: overview and analysis.” 2011. Masters Thesis, Rutgers University. Accessed January 20, 2021.
http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000061509.
MLA Handbook (7th Edition):
Sagar, Nishant, 1986-. “Powerline communications systems: overview and analysis.” 2011. Web. 20 Jan 2021.
Vancouver:
Sagar, Nishant 1. Powerline communications systems: overview and analysis. [Internet] [Masters thesis]. Rutgers University; 2011. [cited 2021 Jan 20].
Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000061509.
Council of Science Editors:
Sagar, Nishant 1. Powerline communications systems: overview and analysis. [Masters Thesis]. Rutgers University; 2011. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000061509
Rutgers University
5.
Škatarić, Maja, 1986-.
Scale invariance in biological systems.
Degree: PhD, Electrical and Computer Engineering, 2014, Rutgers University
URL: https://rucore.libraries.rutgers.edu/rutgers-lib/45463/
► In this dissertation we will discuss various techniques related to modeling and identification problems arising in complex biological networks, and demonstrate how control theory approaches…
(more)
▼ In this dissertation we will discuss various techniques related to modeling and identification problems arising in complex biological networks, and demonstrate how control theory approaches can be used to validate mathematical models coming from exhaustive computational experiments or noisy experimental data. The methodology based on systematic exploration of the basic dynamic processes, feedback control loops, and signal processing mechanisms in complex networks or their parts provides powerful tools for guiding the reverse-engineering of networks, and allows one to design artificial systems that are capable of achieving various objectives. Adaptation is an essential property of many cellular systems and it means that the measured variables return to their basal levels after a transient response to a step increase in stimulus. By definition, neither the concepts of perfect nor approximate adaptation address the characteristics of the transient signaling which occurs prior to a return to steady state, which are physiologically relevant. It has been recently observed that some adapting systems, ranging from bacterial chemotaxis pathways to signal transduction mechanisms in eukaryotes exhibit an additional feature: scale invariance, meaning that transient behavior remains approximately the same when the background signal level is scaled. Recent interest in scale-invariance was triggered by a pair of papers published in 2009, in which scale-invariant behavior was experimentally observed in several highly conserved eukaryotic signaling pathways that play roles in embryonic patterning, stem cell homeostasis, cell division, and other central processes, and their misregulation results in diseases including several types of cancer. In this thesis we will review the biological phenomena of adaptation and scale invariance, and present the relevant mathematical results for several classes of systems that exhibit these properties. We will use a model from the literature which describes the class of enzyme networks, to prove the impossibility of perfect scale invariance, and develop the mechanism which gives rise to an approximate scale invariance. We will demonstrate results on a biological example of soil-living amoeba Dictyostelium discoideum. Additionally, it has been often remarked in the literature that certain systems whose output variables respond at a faster time scale than internal components, give rise to an approximate scale-invariant behavior. We will state a fundamental limitation of such a mechanism, showing that there is a minimal error that cannot be overcome, no matter how large the separation of time scales is. We will highlight the extensions and challenges in analyzing adaptation and scale-invariance in a stochastic setting. Finally, we will discuss the development of tools for the identification of time-varying parameters in nonhomogeneous Poisson processes, in applications where discrete measurements such as "spikes" or "tumbles" are observed from the behavior of free swimming…
Advisors/Committee Members: Sontag, Eduardo (chair), Gajic, Zoran (internal member), Daut, David (internal member), Orfanidis, Sophocles (internal member), Baykal-Gursoy, Melike (outside member).
Subjects/Keywords: Scaling laws (Statistical physics); Control theory; Biological models
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APA ·
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Export
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APA (6th Edition):
Škatarić, Maja, 1. (2014). Scale invariance in biological systems. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/45463/
Chicago Manual of Style (16th Edition):
Škatarić, Maja, 1986-. “Scale invariance in biological systems.” 2014. Doctoral Dissertation, Rutgers University. Accessed January 20, 2021.
https://rucore.libraries.rutgers.edu/rutgers-lib/45463/.
MLA Handbook (7th Edition):
Škatarić, Maja, 1986-. “Scale invariance in biological systems.” 2014. Web. 20 Jan 2021.
Vancouver:
Škatarić, Maja 1. Scale invariance in biological systems. [Internet] [Doctoral dissertation]. Rutgers University; 2014. [cited 2021 Jan 20].
Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/45463/.
Council of Science Editors:
Škatarić, Maja 1. Scale invariance in biological systems. [Doctoral Dissertation]. Rutgers University; 2014. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/45463/
Rutgers University
6.
Sehajpal, Sumati, 1981-.
Design and analysis of class E RF power amplifiers.
Degree: PhD, Electrical and Computer Engineering, 2017, Rutgers University
URL: https://rucore.libraries.rutgers.edu/rutgers-lib/53982/
► The most important stage in a wireless transmitter is the power amplifier because this stage consumes a great deal of power in a wireless system…
(more)
▼ The most important stage in a wireless transmitter is the power amplifier because this stage consumes a great deal of power in a wireless system and is a major factor in the battery life of portable equipment. Generally, switching RF power amplifiers have greater efficiency than their linear counterparts but they are also more difficult to analyze, have switching losses, and can introduce switching transients into the amplified signal. The research focus for this dissertation is on the Class E switching RF power amplifier. This circuit topology uses soft switching in order to minimize switching transients and achieve nearly 100% efficiency in the ideal case. In this dissertation, a short range wireless power transfer system, based on a Class E power converter, is investigated. It operates at 200 kHz and was constructed using commonly available components. A mathematical analysis of a Class E RF power amplifier, operating at 3.9 MHz, is then presented. The model is based on modern state-space techniques and is simulated using both MATLAB and Simulink. Class E RF power amplifiers are insensitive to signal amplitude variations so by itself, this system is only suitable for the amplification of constant envelope signals. This limitation can be overcome, however, with the addition of a supply modulator. One of the most efficient supply modulators is the Class G dual supply modulator. This device utilizes two supply voltages and automatically switches between them depending on signal amplitude. The process of switching from one supply voltage to the other produces transients or ”glitches” that introduce undesirable broadband noise into the signal output. The effects of these glitches, on the noise floor at the Class E power amplifier output, are investigated using a detailed simulation model run on MATLAB. A typical input data stream, glitch depth, and glitch duration are applied to this operating model. As a potential design aid, a purely hypothetical Class E amplifier state-space based model is analyzed based on same simplifying assumptions including a truncated Taylor series expansion of the matrix exponential. Two algebraic equations were derived to determine two Class E amplifier design components. Class E systems are often designed using Raab’s formulas which were derived based on a number of simplifying assumptions. Furthermore, electronic components have tolerances. As a consequence of this a Class E amplifier or power converter must be tuned for proper operation. In order to simplify this process a detailed sensitivity analysis of the Class E circuit topology is presented. This investigation is approached from multiple directions including a state-space based model simulated using MATLAB, a SPICE based simulation, and an experimental Class E prototype operating at 100 kHz.
Advisors/Committee Members: Gajic, Zoran (chair), Caggiano, Michael (internal member), Orfanidis, Sophocles (internal member), Zou, Qingze (internal member), McGarvey, John Joseph (outside member).
Subjects/Keywords: Power amplifiers
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APA (6th Edition):
Sehajpal, Sumati, 1. (2017). Design and analysis of class E RF power amplifiers. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/53982/
Chicago Manual of Style (16th Edition):
Sehajpal, Sumati, 1981-. “Design and analysis of class E RF power amplifiers.” 2017. Doctoral Dissertation, Rutgers University. Accessed January 20, 2021.
https://rucore.libraries.rutgers.edu/rutgers-lib/53982/.
MLA Handbook (7th Edition):
Sehajpal, Sumati, 1981-. “Design and analysis of class E RF power amplifiers.” 2017. Web. 20 Jan 2021.
Vancouver:
Sehajpal, Sumati 1. Design and analysis of class E RF power amplifiers. [Internet] [Doctoral dissertation]. Rutgers University; 2017. [cited 2021 Jan 20].
Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/53982/.
Council of Science Editors:
Sehajpal, Sumati 1. Design and analysis of class E RF power amplifiers. [Doctoral Dissertation]. Rutgers University; 2017. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/53982/
Rutgers University
7.
Hosseini, Mohammad Parsa, 1983-.
Brain-computer interface for analyzing epileptic big data.
Degree: PhD, Electrical and Computer Engineering, 2018, Rutgers University
URL: https://rucore.libraries.rutgers.edu/rutgers-lib/57615/
► Electricity is life but electricity is an invisible fist punching up your spine, knocking your brains right out of your skull." Ray Robinson One percent…
(more)
▼ Electricity is life but electricity is an invisible fist punching up your spine, knocking your brains right out of your skull." Ray Robinson One percent of the world's population suffers from epilepsy, a chronic disorder characterized by the occurrence of spontaneous seizures. About 30 percent of patients remain medically intractable and may undergo surgical intervention; despite the latter, some may still fail to attain a seizure-free outcome. The recent introduction of a closed loop system of localized electroencephalographic (EEG) recording and stimulus delivery (i.e., RNS, Neuropace) has provided greater opportunity to achieve control of this entity although further solutions are required to better actuate the system for optimal efficacy and to bring about an improved quality of life for these patients. A means of therapeutic interaction with an area of epileptogenicity, that does not entail removal of a portion of the brain, first requires adequate detection of ictal (seizure) onset. The use of computers to help physicians in the acquisition, management, storage, and reporting of brain (i.e., EEG) signals is well established. To this end, there are computer-aided detection applications that use a Brain Computer Interface (BCI). In order for a BCI system to work effectively, computational algorithms must reliably identify periods of increased probability of an impending ictal occurrence in order to abort its development. Such preictal periods may be of variable duration and may not afford suitable latency to provide current methodologies with sufficient time for signal deployment to achieve control in all circumstances. The development of an automated method that delivers on such short notice would optimize seizure control and bring about an improved quality of life. Technological innovation with BCI for control of epilepsy must acknowledge the immediacy of seizure occurrence and the time constraints imposed upon effective delivery. The goal of this PhD thesis is to design, develop and implement a BCI autonomic system for epileptic seizure detection and prediction using non-invasive and invasive brain big data. These include real-time data collection, data processing (e.g., feature extraction and classification) by a computer and biofeedback to apply the desired action. The requirements of a practical BCI system include methods for signal processing, machine learning, and brain-state prediction in large data sets collected from user populations in real-time and in combination with their health records. Learning applications of big data in the form of real-time acquisition with the background of the electronic healthcare record (EHR) provide for the generation of new knowledge that will aid in predictions of outcome and, therefore, prognosis. The current and future challenge for BCI centers upon developing methods and systems to remove noise, extract meaningful features and learn from big data. To address existing challenges, we introduce a new method for processing multimodal MRI, rs-fMRI, and EEG…
Advisors/Committee Members: Gajic, Zoran (chair), Orfanidis, Sophocles J. (internal member), Marsic, Ivan (internal member), Elisevich, Kost (outside member), Soltanian-Zadeh, Hamid (outside member), School of Graduate Studies.
Subjects/Keywords: Brain-computer interfaces; Epilepsy
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APA (6th Edition):
Hosseini, Mohammad Parsa, 1. (2018). Brain-computer interface for analyzing epileptic big data. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/57615/
Chicago Manual of Style (16th Edition):
Hosseini, Mohammad Parsa, 1983-. “Brain-computer interface for analyzing epileptic big data.” 2018. Doctoral Dissertation, Rutgers University. Accessed January 20, 2021.
https://rucore.libraries.rutgers.edu/rutgers-lib/57615/.
MLA Handbook (7th Edition):
Hosseini, Mohammad Parsa, 1983-. “Brain-computer interface for analyzing epileptic big data.” 2018. Web. 20 Jan 2021.
Vancouver:
Hosseini, Mohammad Parsa 1. Brain-computer interface for analyzing epileptic big data. [Internet] [Doctoral dissertation]. Rutgers University; 2018. [cited 2021 Jan 20].
Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/57615/.
Council of Science Editors:
Hosseini, Mohammad Parsa 1. Brain-computer interface for analyzing epileptic big data. [Doctoral Dissertation]. Rutgers University; 2018. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/57615/
8.
Kuber, Tejashri, 1988-.
Automatic modulation recognition using the discrete wavelet transform.
Degree: MS, Electrical and Computer Engineering, 2013, Rutgers University
URL: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000068901
► An Automatic Modulation Recognition (AMR) process using the Discrete Wavelet Transform (DWT) is presented in this work. The AMR algorithm involves the use of wavelet…
(more)
▼ An Automatic Modulation Recognition (AMR) process using the Discrete Wavelet Transform (DWT) is presented in this work. The AMR algorithm involves the use of wavelet domain signal templates derived from digitally modulated signals that are used to transmit binary data. The signal templates, locally stored in a receiver, are cross-correlated with the incoming noisy, received signal after it has been transformed into the wavelet domain. The signal template that yields the largest cross-correlation value determines the type of digital modulation that had been employed at the transmitter. The specific binary-valued digital modulation schemes considered in this work include BASK, BFSK and BPSK. The discrete wavelet used for the creation of the signal templates is the Haar, or Daubechies 1, wavelet. Extensive computer simulations have been performed to evaluate the modulation recognition performance of the AMR algorithm as a function of channel SNR. It has been determined that the rate of correct classification for BASK signals is 68% for an SNR = 5 dB and 90% for an SNR = 10 dB SNR. The rate of correct classification for BFSK signals is 71% for an SNR = 5 dB and 92% for an SNR = 10 dB. Correct classification of BPSK signals is 71% for an SNR = 5 dB and 92% for an SNR = 10 dB. In comparison to alternative AMR methods reported in the literature, the AMR algorithm developed in this study produces reliable results even at relatively low values of SNR which are characteristic of realistic communications channels.
Advisors/Committee Members: Kuber, Tejashri, 1988- (author), Daut, David G (chair), Gajic, Zoran (internal member), Orfanidis, Sophocles (internal member).
Subjects/Keywords: Modulators (Electronics)
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APA (6th Edition):
Kuber, Tejashri, 1. (2013). Automatic modulation recognition using the discrete wavelet transform. (Masters Thesis). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000068901
Chicago Manual of Style (16th Edition):
Kuber, Tejashri, 1988-. “Automatic modulation recognition using the discrete wavelet transform.” 2013. Masters Thesis, Rutgers University. Accessed January 20, 2021.
http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000068901.
MLA Handbook (7th Edition):
Kuber, Tejashri, 1988-. “Automatic modulation recognition using the discrete wavelet transform.” 2013. Web. 20 Jan 2021.
Vancouver:
Kuber, Tejashri 1. Automatic modulation recognition using the discrete wavelet transform. [Internet] [Masters thesis]. Rutgers University; 2013. [cited 2021 Jan 20].
Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000068901.
Council of Science Editors:
Kuber, Tejashri 1. Automatic modulation recognition using the discrete wavelet transform. [Masters Thesis]. Rutgers University; 2013. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000068901
9.
Prasanna, Prateek, 1988-.
Computer vision for automated surface evaluation of concrete bridge decks.
Degree: MS, Electrical and Computer Engineering, 2013, Rutgers University
URL: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000068917
► Structural health monitoring of concrete bridges requires accurate and efficient surface crack detection. Early detection of cracks helps prevent further damage. Safety inspection tests are…
(more)
▼ Structural health monitoring of concrete bridges requires accurate and efficient surface crack detection. Early detection of cracks helps prevent further damage. Safety inspection tests are conducted at regular intervals to assess deterioration. Traditional methods involve detection of cracks by human visual inspection. These methods are costly, inefficient and labor intensive, especially for long-span bridges. This thesis presents the use of computer vision and pattern recognition techniques in assessment of cracks on a concrete bridge surface. Bridge deck images are first collected using high-resolution cameras mounted on a robot. Statistical inference algorithms are then implemented to build an automated crack detection system. The proposed machine learning method reduces manual effort and enables automatic labeling over large bridge deck areas to quantify size and location for future reference or comparisons. A panoramic camera is used for the purpose of context localization. Additionally, we demonstrate image-stitching to obtain a coherent spatial mosaic of the bridge deck.
Advisors/Committee Members: Prasanna, Prateek, 1988- (author), Dana, Kristin J (chair), Meer, Peter (internal member), Orfanidis, Sophocles (internal member).
Subjects/Keywords: Structural health monitoring; Computer vision; Concrete bridges – Maintenance and repair; Concrete bridges – Cracking
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APA (6th Edition):
Prasanna, Prateek, 1. (2013). Computer vision for automated surface evaluation of concrete bridge decks. (Masters Thesis). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000068917
Chicago Manual of Style (16th Edition):
Prasanna, Prateek, 1988-. “Computer vision for automated surface evaluation of concrete bridge decks.” 2013. Masters Thesis, Rutgers University. Accessed January 20, 2021.
http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000068917.
MLA Handbook (7th Edition):
Prasanna, Prateek, 1988-. “Computer vision for automated surface evaluation of concrete bridge decks.” 2013. Web. 20 Jan 2021.
Vancouver:
Prasanna, Prateek 1. Computer vision for automated surface evaluation of concrete bridge decks. [Internet] [Masters thesis]. Rutgers University; 2013. [cited 2021 Jan 20].
Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000068917.
Council of Science Editors:
Prasanna, Prateek 1. Computer vision for automated surface evaluation of concrete bridge decks. [Masters Thesis]. Rutgers University; 2013. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000068917
10.
Hajisami, Abolfazl, 1985-.
Dynamic resource allocation for high spectral and energy efficiency in cloud radio access networks.
Degree: PhD, Electrical and Computer Engineering, 2018, Rutgers University
URL: https://rucore.libraries.rutgers.edu/rutgers-lib/57583/
► Over the last few years, the proliferation of personal mobile computing devices like tablets and smartphones along with a plethora of data-intensive mobile applications has…
(more)
▼ Over the last few years, the proliferation of personal mobile computing devices like tablets and smartphones along with a plethora of data-intensive mobile applications has resulted in a tremendous increase in demand for ubiquitous and high data rate wireless communications. However, the system capacity is limited by the radio interference, which makes it difficult to improve the spectral efficiency and consequently the data rate. Current practice to enhance spectral efficiency and data rate is to increase the number of Base Stations (BSs) and go for smaller cells so as to increase the band reuse factor. However, performing additional deployment and maintenance of a large number of cellular BSs is highly inefficient due to excessive capital and operational expenditures. Moreover, with smaller cells the interference problem becomes even more challenging. It is also studied that increasing the BS density or the number of transmit antennas will decrease the energy efficiency due to the dynamic traffic variation. This is because the current cellular architecture is over 40 years old and was not originally designed for high spectral and energy efficiency performance but for coverage and mobility considerations. Cloud Radio Access Network (C-RAN) is a new paradigmatic architecture for wireless cellular networks that allows for dynamic reconfiguration of computing and spectrum resources while keeping the cost of delivering services to the users low. C-RAN consists of three main parts: 1) Remote Radio Heads (RRHs) plus antennae, which are located at the remote site and are controlled by Virtual Base Stations (VBSs) housed in a centralized processing pool, 2) the Base Band Unit (BBU) (known as VBS pool) composed of high-speed programmable processors and real-time virtualization technology to carry out the digital processing tasks, and 3) low-latency high-bandwidth optical fibers, which connect the RRHs to the VBS pool. In a centralized VBS pool, since all the information from the BSs resides in a common place, the VBSs can exchange control data at Gbps. This centralized characteristic along with virtualization technology and low-cost relay-like RRHs provides a higher degree of freedom in order to make optimized decisions; all these features combined have made C-RAN a promising technology candidate to be incorporated into the 5G wireless network standard. The overarching goal of the research presented in this thesis is to design new techniques for increasing the spectral and energy efficiency of the next generation wireless cellular networks. In order to increase the spectral efficiency and energy efficiency, we leverage the C-RAN architecture and propose four solutions, namely 1) Cloud-BSS, 2) DJP, 3) Cloud-CFFR, and 4) Elastic-Net. In Cloud-BSS, we study the performance of Blind Source Separation (BSS) in order to separate the interference from the desired signal and explore how the performance changes in different topologies. Since Cloud-BSS does not take any action to mitigate the…
Advisors/Committee Members: Pompili, Dario (chair), Gajic, Zoran (internal member), Orfanidis, Sophocles (internal member), Masoomzadeh, Ali (outside member), School of Graduate Studies.
Subjects/Keywords: Multiple access protocols (Computer network protocols); Cloud computing
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APA (6th Edition):
Hajisami, Abolfazl, 1. (2018). Dynamic resource allocation for high spectral and energy efficiency in cloud radio access networks. (Doctoral Dissertation). Rutgers University. Retrieved from https://rucore.libraries.rutgers.edu/rutgers-lib/57583/
Chicago Manual of Style (16th Edition):
Hajisami, Abolfazl, 1985-. “Dynamic resource allocation for high spectral and energy efficiency in cloud radio access networks.” 2018. Doctoral Dissertation, Rutgers University. Accessed January 20, 2021.
https://rucore.libraries.rutgers.edu/rutgers-lib/57583/.
MLA Handbook (7th Edition):
Hajisami, Abolfazl, 1985-. “Dynamic resource allocation for high spectral and energy efficiency in cloud radio access networks.” 2018. Web. 20 Jan 2021.
Vancouver:
Hajisami, Abolfazl 1. Dynamic resource allocation for high spectral and energy efficiency in cloud radio access networks. [Internet] [Doctoral dissertation]. Rutgers University; 2018. [cited 2021 Jan 20].
Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/57583/.
Council of Science Editors:
Hajisami, Abolfazl 1. Dynamic resource allocation for high spectral and energy efficiency in cloud radio access networks. [Doctoral Dissertation]. Rutgers University; 2018. Available from: https://rucore.libraries.rutgers.edu/rutgers-lib/57583/
11.
Namboodiri, Vamadevan, 1967-.
Low complexity iterative receiver design for OFDM systems.
Degree: Electrical and Computer Engineering, 2012, Rutgers University
URL: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000065232
Subjects/Keywords: MIMO systems; Wireless communication systems
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APA (6th Edition):
Namboodiri, Vamadevan, 1. (2012). Low complexity iterative receiver design for OFDM systems. (Thesis). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000065232
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Namboodiri, Vamadevan, 1967-. “Low complexity iterative receiver design for OFDM systems.” 2012. Thesis, Rutgers University. Accessed January 20, 2021.
http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000065232.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Namboodiri, Vamadevan, 1967-. “Low complexity iterative receiver design for OFDM systems.” 2012. Web. 20 Jan 2021.
Vancouver:
Namboodiri, Vamadevan 1. Low complexity iterative receiver design for OFDM systems. [Internet] [Thesis]. Rutgers University; 2012. [cited 2021 Jan 20].
Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000065232.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Namboodiri, Vamadevan 1. Low complexity iterative receiver design for OFDM systems. [Thesis]. Rutgers University; 2012. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000065232
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
12.
Kremo, Haris, 1970-.
On the spatial and temporal coherence of wireless
vehicular short range channels.
Degree: PhD, Electrical and Computer Engineering, 2011, Rutgers University
URL: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000057607
► We consider spatial and temporal coherence of the vehicle–to–vehicle (V2V) wireless communication channel with focus on a suburban residential highway. The dominant reflectors in such…
(more)
▼ We consider spatial and temporal coherence of the vehicle–to–vehicle (V2V) wireless communication channel with focus on a suburban residential highway. The dominant reflectors in such an environment are vehicles passing in the adjacent lane and houses
along the road. Instead of treating the reflectors as point targets, the V2V short range propagation environment requires partitioning of the illuminated reflector side into
sufficiently small tiles. The channel transfer function is obtained as a superposition of specular reflections from the tiles, the line–of–sight (LOS) component, and the ground reflection. The tile size is selected to ensure that the ratio of the tile area to the tile–to–receiver distance satisfies the far field conditions. The reflected power is described by the tile radar cross section (RCS). The bistatic physical optics RCS model is adapted to account for the tile’s orientation with respect to the ray geometry. We apply the superposition model to the numerical analysis of two general scenarios
for a 22MHz channel in the 2.4GHz band. The first scenario considers a single vehicle reflector passing in the lane adjacent to the V2V communication pair. Both the vector network analyzer (VNA) experiments and the tiling model analysis illustrate that repositioning of the reflector, the transmitter, or the receiver by a few centimeters results in change of the signal power by several decibels. The second scenario analysis characterizes the channel coherence statistics for the
suburban residential highway. We consider the V2V single lane LOS and non–LOS geometries, where in the latter the receiver is shadowed by a large vehicle. The reflectors are both houses and vehicles passing in the opposite direction. The measure of channel coherence is the normalized spatial covariance calculated by correlating transfer functions corresponding to feasible receiver position pairs and performing spatial smoothing. The area of feasible receiver positions is divided into contiguous squares
whose size ensures wide sense quasi–stationarity within the square. Irrespective of direction the correlation remains high and a typical sedan roof usually does not provide sufficient spacing to obtain average inter–antenna correlation lower than 0.5. The upper bound on coherence time extends over the transmission time of multiple packets for systems in the considered band, and does not allow for usable time diversity.
Advisors/Committee Members: Kremo, Haris, 1970- (author), Spasojevic, Predrag (chair), Greenstein, Larry J (internal member), Orfanidis, Sophocles J (internal member), Yates, Roy D (internal member), Chizhik, Dmitry (outside member).
Subjects/Keywords: Radar cross sections; Spatial data infrastructures; Wireless communication systems
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APA (6th Edition):
Kremo, Haris, 1. (2011). On the spatial and temporal coherence of wireless
vehicular short range channels. (Doctoral Dissertation). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000057607
Chicago Manual of Style (16th Edition):
Kremo, Haris, 1970-. “On the spatial and temporal coherence of wireless
vehicular short range channels.” 2011. Doctoral Dissertation, Rutgers University. Accessed January 20, 2021.
http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000057607.
MLA Handbook (7th Edition):
Kremo, Haris, 1970-. “On the spatial and temporal coherence of wireless
vehicular short range channels.” 2011. Web. 20 Jan 2021.
Vancouver:
Kremo, Haris 1. On the spatial and temporal coherence of wireless
vehicular short range channels. [Internet] [Doctoral dissertation]. Rutgers University; 2011. [cited 2021 Jan 20].
Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000057607.
Council of Science Editors:
Kremo, Haris 1. On the spatial and temporal coherence of wireless
vehicular short range channels. [Doctoral Dissertation]. Rutgers University; 2011. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000057607
13.
Madan, Siddharth K., 1984-.
Computer vision methods for large-scale online clustering and quantitative dermatology.
Degree: Electrical and Computer Engineering, 2013, Rutgers University
URL: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000068911
Subjects/Keywords: Computer vision; Dermatology – Data processing; Database management
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APA (6th Edition):
Madan, Siddharth K., 1. (2013). Computer vision methods for large-scale online clustering and quantitative dermatology. (Thesis). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000068911
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Madan, Siddharth K., 1984-. “Computer vision methods for large-scale online clustering and quantitative dermatology.” 2013. Thesis, Rutgers University. Accessed January 20, 2021.
http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000068911.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Madan, Siddharth K., 1984-. “Computer vision methods for large-scale online clustering and quantitative dermatology.” 2013. Web. 20 Jan 2021.
Vancouver:
Madan, Siddharth K. 1. Computer vision methods for large-scale online clustering and quantitative dermatology. [Internet] [Thesis]. Rutgers University; 2013. [cited 2021 Jan 20].
Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000068911.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Madan, Siddharth K. 1. Computer vision methods for large-scale online clustering and quantitative dermatology. [Thesis]. Rutgers University; 2013. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000068911
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Rutgers University
14.
Leondopulos, Stathis S.
A study on adaptive stimulation of the basal ganglia as a treatment for Parkinsonism.
Degree: PhD, Electrical and Computer Engineering, 2007, Rutgers University
URL: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.16722
► The purpose of this dissertation is to design an automated system for the modification of Deep Brain Stimulation (DBS) parameters based on specific identifiers in…
(more)
▼ The purpose of this dissertation is to design an automated system for the modification of Deep Brain Stimulation (DBS) parameters based on specific identifiers in the neuronal response of Parkinsonian patients undergoing DBS treatment. The neural response patterns are obtained from an artificial neural network consisting of dynamic neuron and synapse components and programmed to exhibit a response to pulse stimuli that resembles the activity in the subthalamic nucleus of Parkinsonian patients undergoing DBS treatment. Moreover, using pulse stimuli of varying specification, a band-pass filtered response of the network is subjected to a set of signal processing techniques including Linear Predictive Coding (LPC), Autoregressive Moving Average (ARMA) modeling, Discrete Fourier Transform (DFT), moments and higher order statistics, producing a set of results or features. Then, each feature is evaluated to determine the effectiveness, in terms of error probability, of discerning between different neuronal responses to pulse stimuli. Furthermore, a digital circuit is designed at the transistor level for computing the 1st LPC coefficient of recorded neural data and also autonomously regulating the specifications of the stimulus waveform based on the value of the computed coefficient. Also, the circuit design is optimized using a pipeline to reduce dynamic power dissipation. Moreover, it is suggested that a similar design may be useful in automating the administration of DBS as a treatment for Parkinsonism with only a minimal additional power demand.
Advisors/Committee Members: Leondopulos, Stathis S. (author), Micheli-Tzanakou, Evangelia (chair), Bushnell, Michael (internal member), Gajic, Zoran (internal member), Caggiano, Michael (internal member), Orfanidis, Sophocles (internal member), Nowakowski, Richard (outside member).
Subjects/Keywords: Brain stimulation
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APA (6th Edition):
Leondopulos, S. S. (2007). A study on adaptive stimulation of the basal ganglia as a treatment for Parkinsonism. (Doctoral Dissertation). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.16722
Chicago Manual of Style (16th Edition):
Leondopulos, Stathis S. “A study on adaptive stimulation of the basal ganglia as a treatment for Parkinsonism.” 2007. Doctoral Dissertation, Rutgers University. Accessed January 20, 2021.
http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.16722.
MLA Handbook (7th Edition):
Leondopulos, Stathis S. “A study on adaptive stimulation of the basal ganglia as a treatment for Parkinsonism.” 2007. Web. 20 Jan 2021.
Vancouver:
Leondopulos SS. A study on adaptive stimulation of the basal ganglia as a treatment for Parkinsonism. [Internet] [Doctoral dissertation]. Rutgers University; 2007. [cited 2021 Jan 20].
Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.16722.
Council of Science Editors:
Leondopulos SS. A study on adaptive stimulation of the basal ganglia as a treatment for Parkinsonism. [Doctoral Dissertation]. Rutgers University; 2007. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.16722
Rutgers University
15.
Maloor, Srinivas P.
Statistical strategies for scaling and weighting variables for cluster analysis.
Degree: PhD, Electrical and Computer Engineering, 2007, Rutgers University
URL: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.16739
► Cluster analysis (CA) is a generic name for an array of quantitative methods, the applications of which are found in numerous fields ranging from astronomy…
(more)
▼ Cluster analysis (CA) is a generic name for an array of quantitative methods, the applications of which are found in numerous fields ranging from astronomy and biology to finance and psychology. Though the intuitive idea of clustering is clear enough, the details of actually carrying out such an analysis entail many unresolved conceptual problems. Multivariate data, often poses a problem, in that the variables are not commensurate. Since the outcome of a CA is sensitive to the scales of measurement of the input data, many practitioners resort to standardizing the data prior to the analysis. Hence, the scaling of such multivariate data prior to CA is important as a preprocessing step. Autoscaling, is one such naive approach. Although it is a widely used procedure to standardize variables in some major point and click statistical software packages, it ignores the inherent cluster structure and actually proves counterproductive.
This dissertation is broadly divided into two parts - Univariate and Multivariate strategies. The first part addresses some univariate scaling and weighting approaches. In an attempt to put all variables on the same footing, we propose some intuitive strategies which we call equalizers. In addition, we consider letting the data suggest weights or highlighters that emphasize those variables with most promise for revealing the latent cluster structure. The methods vary in degree of complexity from simple weights based on order statistics to more complicated iterative ones. The results indicate that, in a variety of chosen simulated data as well as real data sets, the new methods are much better than the most popular method, autoscaling. Although these strategies are computationally appealing, they are at best suboptimal in their ability to unearth the latent clusters embedded in the multivariate structure of the data. Hence, the next part of this dissertation is devoted to multivariate scaling and weighting approaches. We perform a systematic study of the characteristics of a multivariate equalizer in both the null-cluster scenario and for a variety of cluster structures. In addition, we present a multivariate approach to perform variable highlighting that is validated by results from many simulated data sets as well as some real data sets. Taken together, our results indicate that simple and intuitive strategies to preprocess data sets render them amenable to superior cluster recovery.
Advisors/Committee Members: Maloor, Srinivas P. (author), Madigan, David (chair), Orfanidis, Sophocles (internal member), Wilder, Joseph (internal member), Kettenring, Jon (outside member), Gnanadesikan, Ramanathan (outside member).
Subjects/Keywords: Cluster analysis; Multivariate analysis
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APA (6th Edition):
Maloor, S. P. (2007). Statistical strategies for scaling and weighting variables for cluster analysis. (Doctoral Dissertation). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.16739
Chicago Manual of Style (16th Edition):
Maloor, Srinivas P. “Statistical strategies for scaling and weighting variables for cluster analysis.” 2007. Doctoral Dissertation, Rutgers University. Accessed January 20, 2021.
http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.16739.
MLA Handbook (7th Edition):
Maloor, Srinivas P. “Statistical strategies for scaling and weighting variables for cluster analysis.” 2007. Web. 20 Jan 2021.
Vancouver:
Maloor SP. Statistical strategies for scaling and weighting variables for cluster analysis. [Internet] [Doctoral dissertation]. Rutgers University; 2007. [cited 2021 Jan 20].
Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.16739.
Council of Science Editors:
Maloor SP. Statistical strategies for scaling and weighting variables for cluster analysis. [Doctoral Dissertation]. Rutgers University; 2007. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.16739
Rutgers University
16.
Chen, Hou-Shin.
Spectrum sensing for wireless broadcast communication systems.
Degree: PhD, Electrical and Computer Engineering, 2008, Rutgers University
URL: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.17288
► Spectrum sensing is the methodology used to determine the existence of a specific signal type in very low signal to noise power ratio (SNR) environments.…
(more)
▼ Spectrum sensing is the methodology used to determine the existence of a specific signal type in very low signal to noise power ratio (SNR) environments. Spectrum sensing is one of the core technologies for the application of Cognitive Radio (CR). An IEEE 802.22 Working Group has developed a Standard to implement CR in the wireless services spectrum. The spectrum, however, has already been allocated to the TV Broadcast Service which delivers ATSC Digital TV (DTV) signals. Cognitive Radio systems are intended to co-exist within the spectrum licensed to TV channels and operate on a non-interfering basis. At present, there are three TV broadcast Standards worldwide, namely the ATSC DTV Standard [1], ETSI DVB-T Standard [2], and the NSPRC DMB-T Standard [3]. The transmitted signals defined by these three Standards possess different characteristics. Thus, in order to apply CR in the DTV bands, different spectrum sensing techniques are needed for these three broadcast Standards. In this thesis, the focus is on the development of suitable spectrum sensing algorithms for the DTV signals defined by these three Standards. In addition, wireless microphone devices use frequency bands that are located within the allocated DTV bands. Cognitive Radio systems should transmit and receive using spectrum that is idle. Hence, in this thesis, spectrum sensing algorithms are also designed to detect the presence of wireless microphone signals. When developing an algorithm to perform spectrum sensing for a
specific signal, we make use of particular characteristics embedded in the transmitted signals to design effective detector structures that can discriminate between the presence or absence of licensed information bearing signals. One useful method employed in this thesis is to utilize the cyclostationary property that is present in most of the transmitted
data signals to perform spectrum sensing. Additionally, the probability of false alarm and probability of misdetection performance metrics for signal detectors employing different spectrum sensing algorithms are analyzed. The spectrum sensor operating characteristic curves for the different detectors are demonstrated by the use of computer simulations. Simulation results indicate that the spectrum sensing algorithms developed in this thesis can efficiently detect the presence of primary licensed signals when the SNR is as low as -20 dB. Finally, selected spectrum sensing algorithms are implemented using an FPGA-based hardware platform. The hardware implementation of the spectrum sensors verified their performance, as well as demonstrated their practicality due to the low complexity of the algorithms.
Advisors/Committee Members: Chen, Hou-Shin (author), Daut, David (chair), Orfanidis, Sophocles (internal member), Spasojevic, Predrag (internal member), Marsic, Ivan (internal member), Gao, Wen (outside member).
Subjects/Keywords: Wireless communication systems
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APA (6th Edition):
Chen, H. (2008). Spectrum sensing for wireless broadcast communication systems. (Doctoral Dissertation). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.17288
Chicago Manual of Style (16th Edition):
Chen, Hou-Shin. “Spectrum sensing for wireless broadcast communication systems.” 2008. Doctoral Dissertation, Rutgers University. Accessed January 20, 2021.
http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.17288.
MLA Handbook (7th Edition):
Chen, Hou-Shin. “Spectrum sensing for wireless broadcast communication systems.” 2008. Web. 20 Jan 2021.
Vancouver:
Chen H. Spectrum sensing for wireless broadcast communication systems. [Internet] [Doctoral dissertation]. Rutgers University; 2008. [cited 2021 Jan 20].
Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.17288.
Council of Science Editors:
Chen H. Spectrum sensing for wireless broadcast communication systems. [Doctoral Dissertation]. Rutgers University; 2008. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.17288
Rutgers University
17.
Subbarao, Raghav.
Robust statistics over Riemannian manifolds for computer vision.
Degree: PhD, Electrical and Computer Engineering, 2008, Rutgers University
URL: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.17398
► The nonlinear nature of many compute vision tasks involves analysis over curved nonlinear spaces embedded in higher dimensional Euclidean spaces. Such spaces are known as…
(more)
▼ The nonlinear nature of many compute vision tasks involves analysis over curved nonlinear spaces embedded in higher dimensional Euclidean spaces. Such spaces are known as manifolds and can be studied using the theory of differential geometry. In this thesis we develop two algorithms which can be applied over manifolds.
The nonlinear mean shift algorithm is a generalization of the original mean shift, a popular feature space analysis method for vector spaces. Nonlinear mean shift can be applied to any Riemannian manifold and is provably convergent to the local maxima of an appropriate kernel density. This algorithm is used for motion segmentation with different motion models and for the filtering of complex image data.
The projection based M-estimator is a robust regression algorithm which does not require a user supplied estimate of the scale, the level of noise corrupting the inliers. We build on the connections between kernel density estimation and robust M-estimators and develop data driven rules for scale estimation. The method can be generalized to handle heteroscedastic data and subspace estimation. The results of using pbM for affine motion estimation, fundamental matrix estimation and multibody factorization are presented.
A new sensor fusion method which can handle heteroscedastic data and incomplete estimates of parameters is also discussed. The method is used to combine image based pose estimates with inertial sensors.
Advisors/Committee Members: Subbarao, Raghav (author), Meer, Peter (chair), Dana, Kristin (internal member), Orfanidis, Sophocles (internal member), Trappe, Wade (internal member), Genc, Yakup (outside member).
Subjects/Keywords: Robust statistics; Riemannian manifolds; Computer vision
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APA (6th Edition):
Subbarao, R. (2008). Robust statistics over Riemannian manifolds for computer vision. (Doctoral Dissertation). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.17398
Chicago Manual of Style (16th Edition):
Subbarao, Raghav. “Robust statistics over Riemannian manifolds for computer vision.” 2008. Doctoral Dissertation, Rutgers University. Accessed January 20, 2021.
http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.17398.
MLA Handbook (7th Edition):
Subbarao, Raghav. “Robust statistics over Riemannian manifolds for computer vision.” 2008. Web. 20 Jan 2021.
Vancouver:
Subbarao R. Robust statistics over Riemannian manifolds for computer vision. [Internet] [Doctoral dissertation]. Rutgers University; 2008. [cited 2021 Jan 20].
Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.17398.
Council of Science Editors:
Subbarao R. Robust statistics over Riemannian manifolds for computer vision. [Doctoral Dissertation]. Rutgers University; 2008. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.17398
Rutgers University
18.
Ho, Ka Mun.
Automatic recognition and demodulation of digitally modulated communications signals using wavelet-domain signatures:.
Degree: PhD, Electrical and Computer Engineering, 2010, Rutgers University
URL: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052117
► Wavelet transform-based methodologies for both Automatic Modulation Recognition (AMR) and Demodulation of digitally modulated communications signals can be utilized in an enabling platform for the…
(more)
▼ Wavelet transform-based methodologies for both Automatic Modulation Recognition (AMR) and Demodulation of digitally modulated communications signals can be utilized in an enabling platform for the implementation of a new class of communications systems. In particular, such techniques could enable the development of agile radio transceivers for use in both commercial and military applications. Such radio transceivers would have the ability to transmit and receive signals using many different modulation schemes while employing a common receiver architecture based on a single demodulator.
In this dissertation, the development of AMR and Demodulation techniques are based on the relatively new mathematical theory of Wavelet Transforms (WTs). Information-bearing signals acquired by communications receivers are transformed into the wavelet-domain using the Continuous Wavelet Transform (CWT) and then applied to signal processing algorithms that also use the CWT in conjunction with pattern recognition techniques. In particular, the method of template-matching is used for both the AMR and Demodulation processes. Signal templates characterizing various modulated signals are used for both processes. The signal templates are determined based on the signal features present in the fractal patterns of their corresponding scalograms for specific modulation schemes as they appear in the wavelet-domain. The algorithms developed in this work are capable of both classifying the method of modulation used in the acquired signal, as well as subsequently automatically demodulating the signal to recover the message.
The classes of digitally modulated signals considered in this work include variants of the Amplitude-, Frequency-, Phase-Shift Keying modulation families, i.e., ASK, FSK, and PSK, respectively, and multiple-level Quadrature Amplitude Modulation (M-ary QAM) families. The AMR and Demodulation performances are evaluated in the presence of Additive White Gaussian Noise (AWGN) over a wide range of Signal-to-Noise Ratio (SNR) values. Through extensive Monte Carlo computer simulations it is determined that the average correct classification rates using wavelet-based AMR for PSK, ASK, and QAM are over 98%, and over 90% for FSK signals, all at an SNR of 0 dB. The Bit Error Rate (BER) performance obtained using wavelet-based Demodulation is at least one order of magnitude better than the matched filter-based BER performance realized for the modulation schemes considered.
Advisors/Committee Members: Ho, Ka Mun, (author), Daut, David (chair), Gajic, Zoran (internal member), Orfanidis, Sophocles (internal member), Rabiner, Lawrence, (internal member), Madabushi, Anant (outside member).
Subjects/Keywords: Modulation (Electronics); Pattern recognition systems; Signal processing
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APA (6th Edition):
Ho, K. M. (2010). Automatic recognition and demodulation of digitally modulated communications signals using wavelet-domain signatures:. (Doctoral Dissertation). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052117
Chicago Manual of Style (16th Edition):
Ho, Ka Mun. “Automatic recognition and demodulation of digitally modulated communications signals using wavelet-domain signatures:.” 2010. Doctoral Dissertation, Rutgers University. Accessed January 20, 2021.
http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052117.
MLA Handbook (7th Edition):
Ho, Ka Mun. “Automatic recognition and demodulation of digitally modulated communications signals using wavelet-domain signatures:.” 2010. Web. 20 Jan 2021.
Vancouver:
Ho KM. Automatic recognition and demodulation of digitally modulated communications signals using wavelet-domain signatures:. [Internet] [Doctoral dissertation]. Rutgers University; 2010. [cited 2021 Jan 20].
Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052117.
Council of Science Editors:
Ho KM. Automatic recognition and demodulation of digitally modulated communications signals using wavelet-domain signatures:. [Doctoral Dissertation]. Rutgers University; 2010. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052117
Rutgers University
19.
Vaz, Canute.
Estimation and equalization of communications channels using wavelet transforms:.
Degree: PhD, Electrical and Computer Engineering, 2010, Rutgers University
URL: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052157
► This dissertation features the development of signal processing strategies for the estimation of the impulse responses of channels and the equalization of the effects of…
(more)
▼ This dissertation features the development of signal processing strategies for the estimation of the impulse responses of channels and the equalization of the effects of channels on communications signals propagating through them using the Discrete Wavelet Transform (DWT). The two strategies are developed as part of a wavelet-based signal processing platform, which can be used to enable reconfigurable radio transceivers.
In broad terms, the approach that is taken is to recast standard discrete time-domain signal processing procedures into a DWT-based framework. To facilitate this, three equivalent techniques of DWT-based convolution are devised. The techniques are described analytically using a systems-theoretic approach. The convolution techniques use both standard subband coding as well as polyphase filter implementations.
Consequent to the development of DWT-based convolution is a DWT-based deconvolution procedure that is derived analytically. The deconvolution procedure is then applied to the problem of the estimation of several time-invariant multipath communications channels. Conditions of slow and fast fading are considered, and faded test signals are also subjected to Additive White Gaussian Noise (AWGN) that result in ratios of bit-energy-to-noise-power-density, Eb/N0, in the range of 0 to 60 dB. Monte Carlo simulations of the estimation of the channel impulse responses yield Mean-Square Error (MSE) results with excellent statistical agreement even for coarse levels of DWT resolution when compared with standard discrete time-domain deconvolution.
Using DWT-based convolution the linear equalization techniques of Zero Forcing Equalization (ZFE) and Minimum Mean-Squared Error (MMSE) equalization, are formulated and implemented in the wavelet-domain. Monte Carlo simulations of the equalization of a fast fading channel with Eb/N0 in the range from 0 dB to 60 dB show that the performance of both linear equalizers in the time and wavelet-domains is essentially identical.
Allied with the primary objective of the dissertation, both DWT-based channel estimation and equalization are included in communications systems. In Monte Carlo simulations of these systems, signals that are digitally modulated with the Binary Amplitude Shift Keying (BASK), Binary Frequency Shift Keying (BFSK) and 16-Quadrature Amplitude Modulation (16-QAM) schemes are propagated through a fast fading channel. The faded signals are subjected to AWGN resulting in Eb/N0 in the range from 0 dB to 20 dB. The performance of these hybrid time- and DWT-based communications systems is evaluated with Symbol Error Rate (SER) curves that show no decrease in performance when compared with discrete time-domain system methods.
Advisors/Committee Members: Vaz, Canute (author), Daut, David (chair), McAfee, Sigrid (internal member), Orfanidis, Sophocles (internal member), Sannuti, Peddapullaiah (internal member), Chant, Robert, (outside member).
Subjects/Keywords: Signal processing; Wavelets (Mathematics)
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Record Details
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❌
APA ·
Chicago ·
MLA ·
Vancouver ·
CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Vaz, C. (2010). Estimation and equalization of communications channels using wavelet transforms:. (Doctoral Dissertation). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052157
Chicago Manual of Style (16th Edition):
Vaz, Canute. “Estimation and equalization of communications channels using wavelet transforms:.” 2010. Doctoral Dissertation, Rutgers University. Accessed January 20, 2021.
http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052157.
MLA Handbook (7th Edition):
Vaz, Canute. “Estimation and equalization of communications channels using wavelet transforms:.” 2010. Web. 20 Jan 2021.
Vancouver:
Vaz C. Estimation and equalization of communications channels using wavelet transforms:. [Internet] [Doctoral dissertation]. Rutgers University; 2010. [cited 2021 Jan 20].
Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052157.
Council of Science Editors:
Vaz C. Estimation and equalization of communications channels using wavelet transforms:. [Doctoral Dissertation]. Rutgers University; 2010. Available from: http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052157
Rutgers University
20.
Mittal, Sushil, 1982-.
User-independent robust statistics for computer vision.
Degree: Electrical and Computer Engineering, 2011, Rutgers University
URL: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000063533
Subjects/Keywords: Robust optimization; Computer vision
Record Details
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Record Details
Similar Records
Cite
« Share
❌
APA ·
Chicago ·
MLA ·
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CSE |
Export
to Zotero / EndNote / Reference
Manager
APA (6th Edition):
Mittal, Sushil, 1. (2011). User-independent robust statistics for computer vision. (Thesis). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000063533
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Chicago Manual of Style (16th Edition):
Mittal, Sushil, 1982-. “User-independent robust statistics for computer vision.” 2011. Thesis, Rutgers University. Accessed January 20, 2021.
http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000063533.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
MLA Handbook (7th Edition):
Mittal, Sushil, 1982-. “User-independent robust statistics for computer vision.” 2011. Web. 20 Jan 2021.
Vancouver:
Mittal, Sushil 1. User-independent robust statistics for computer vision. [Internet] [Thesis]. Rutgers University; 2011. [cited 2021 Jan 20].
Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000063533.
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
Council of Science Editors:
Mittal, Sushil 1. User-independent robust statistics for computer vision. [Thesis]. Rutgers University; 2011. Available from: http://hdl.rutgers.edu/1782.1/rucore10001600001.ETD.000063533
Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation
. 
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