subject:(nonlinear filtering)

University of New Mexico

1. Cook, Robert. Continuous Measurement and Stochastic Methods in Quantum Optical Systems.

Degree: Physics & Astronomy, 2013, University of New Mexico

URL: http://hdl.handle.net/1928/23093

► This dissertation studies the statistics and modeling of a quantum system probed by a coherent laser field. We focus on an ensemble of qubits dispersively… (more)

▼ This dissertation studies the statistics and modeling of a quantum system probed by a coherent laser field. We focus on an ensemble of qubits dispersively coupled to a traveling wave light field. The first research topic explores the quantum measurement statistics of a quasi-monochromatic laser probe. We identify the shortest timescale that successive measurements approximately commute. Our model predicts that for a probe in the near infrared, noncommuting measurement effects are apparent for subpicosecond times. The second dissertation topic attempts to find an approximation to a conditional master equation, which maps identical product states to identical product states. Through a technique known as projection filtering, we find such a equation for an ensemble of qubits experiencing a diffusive measurement of a collective angular momentum projection, in addition to global rotations. We then test the quality of the approximation through numerical simulations. This measurement model is known to be entangling and without the rotations we find poor agreement between the exact and approximate predictions. However, in the presence of strong randomized rotations, the approximation reproduces the exact expectation values to within 95% accuracy. The final topic applies the projection filter to the problem of state reconstruction. We find an initial state estimate based on a single continuous measurement of an identically prepared atomic ensemble. Given the ability to make a continuous collective measurement and simultaneously applying time varying controls, it is possible to find an accurate estimate given based upon a single measurement realization. Previous experiments implementing this method found high fidelity estimates, but were ultimately limited by decoherence. Here we explore the fundamental limits of this protocol by studying an idealized model for pure qubits, which is limited only by measurement backaction. This ultimately makes the measurement statistics a nonlinear function of the initial state. Via the projection filter, we find an efficiently computed approximation to the log-likelihood function. Using the exact dynamics to produce simulated measurements, we then numerically search for a maximum likelihood estimate based on the approximate expression. We ultimately find that our estimation technique nearly achieves an average fidelity bound set by an optimum POVM. Advisors/Committee Members: Deutsch, Ivan, Prasad, Sudhakar, Loring, Terry, Carlton, Caves.

Subjects/Keywords: Quantum measurement; Quantum tomography; nonlinear filtering

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APA (6^th Edition):

Cook, R. (2013). Continuous Measurement and Stochastic Methods in Quantum Optical Systems. (Doctoral Dissertation). University of New Mexico. Retrieved from http://hdl.handle.net/1928/23093

Chicago Manual of Style (16^th Edition):

Cook, Robert. “Continuous Measurement and Stochastic Methods in Quantum Optical Systems.” 2013. Doctoral Dissertation, University of New Mexico. Accessed March 04, 2021. http://hdl.handle.net/1928/23093.

MLA Handbook (7^th Edition):

Cook, Robert. “Continuous Measurement and Stochastic Methods in Quantum Optical Systems.” 2013. Web. 04 Mar 2021.

Vancouver:

Cook R. Continuous Measurement and Stochastic Methods in Quantum Optical Systems. [Internet] [Doctoral dissertation]. University of New Mexico; 2013. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1928/23093.

Council of Science Editors:

Cook R. Continuous Measurement and Stochastic Methods in Quantum Optical Systems. [Doctoral Dissertation]. University of New Mexico; 2013. Available from: http://hdl.handle.net/1928/23093

California State University – Northridge

2. Zambri, Brian. Mathematical Analysis and Numerical Computation of the Brain Response to Single-Event-Related Stimuli.

Degree: MS, Department of Mathematics, 2015, California State University – Northridge

URL: http://hdl.handle.net/10211.3/141810

► The goal of this study is to analyze mathematically and numerically the hemodynamic mathematical model that describes changes in blood flow and blood oxygenation during… (more)

Subjects/Keywords: nonlinear filtering; Dissertations, Academic – CSUN – Mathematics.

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APA (6^th Edition):

Zambri, B. (2015). Mathematical Analysis and Numerical Computation of the Brain Response to Single-Event-Related Stimuli. (Masters Thesis). California State University – Northridge. Retrieved from http://hdl.handle.net/10211.3/141810

Chicago Manual of Style (16^th Edition):

Zambri, Brian. “Mathematical Analysis and Numerical Computation of the Brain Response to Single-Event-Related Stimuli.” 2015. Masters Thesis, California State University – Northridge. Accessed March 04, 2021. http://hdl.handle.net/10211.3/141810.

MLA Handbook (7^th Edition):

Zambri, Brian. “Mathematical Analysis and Numerical Computation of the Brain Response to Single-Event-Related Stimuli.” 2015. Web. 04 Mar 2021.

Vancouver:

Zambri B. Mathematical Analysis and Numerical Computation of the Brain Response to Single-Event-Related Stimuli. [Internet] [Masters thesis]. California State University – Northridge; 2015. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10211.3/141810.

Council of Science Editors:

Zambri B. Mathematical Analysis and Numerical Computation of the Brain Response to Single-Event-Related Stimuli. [Masters Thesis]. California State University – Northridge; 2015. Available from: http://hdl.handle.net/10211.3/141810

University of Tennessee – Knoxville

3. Li, Zhiqiang. Stability of Nonlinear Filters and Branching Particle Approximations to The Filtering Problems.

Degree: 2012, University of Tennessee – Knoxville

URL: https://trace.tennessee.edu/utk_graddiss/1322

► Various particle filters have been proposed and their convergence to the optimal filter are obtained for finite time intervals. However, uniform convergence results have been… (more)

Subjects/Keywords: nonlinear filtering; branching particle aproximation; Probability

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APA (6^th Edition):

Li, Z. (2012). Stability of Nonlinear Filters and Branching Particle Approximations to The Filtering Problems. (Doctoral Dissertation). University of Tennessee – Knoxville. Retrieved from https://trace.tennessee.edu/utk_graddiss/1322

Chicago Manual of Style (16^th Edition):

Li, Zhiqiang. “Stability of Nonlinear Filters and Branching Particle Approximations to The Filtering Problems.” 2012. Doctoral Dissertation, University of Tennessee – Knoxville. Accessed March 04, 2021. https://trace.tennessee.edu/utk_graddiss/1322.

MLA Handbook (7^th Edition):

Li, Zhiqiang. “Stability of Nonlinear Filters and Branching Particle Approximations to The Filtering Problems.” 2012. Web. 04 Mar 2021.

Vancouver:

Li Z. Stability of Nonlinear Filters and Branching Particle Approximations to The Filtering Problems. [Internet] [Doctoral dissertation]. University of Tennessee – Knoxville; 2012. [cited 2021 Mar 04]. Available from: https://trace.tennessee.edu/utk_graddiss/1322.

Council of Science Editors:

Li Z. Stability of Nonlinear Filters and Branching Particle Approximations to The Filtering Problems. [Doctoral Dissertation]. University of Tennessee – Knoxville; 2012. Available from: https://trace.tennessee.edu/utk_graddiss/1322

University of Southern California

4. Johnson, Daniel M. The wavelet filter: a new method for nonlinear, nongaussian filtering in one dimension.

Degree: MS, Computer Science, 2009, University of Southern California

URL: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/172277/rec/7408

► While classical orthogonal function systems (COFS) are very successful at approximating static functions, there are several problems with using them in multi-stage estimation. These problems… (more)

Subjects/Keywords: nonlinear estimation; nonlinear filtering; wavelets

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APA (6^th Edition):

Johnson, D. M. (2009). The wavelet filter: a new method for nonlinear, nongaussian filtering in one dimension. (Masters Thesis). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/172277/rec/7408

Chicago Manual of Style (16^th Edition):

Johnson, Daniel M. “The wavelet filter: a new method for nonlinear, nongaussian filtering in one dimension.” 2009. Masters Thesis, University of Southern California. Accessed March 04, 2021. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/172277/rec/7408.

MLA Handbook (7^th Edition):

Johnson, Daniel M. “The wavelet filter: a new method for nonlinear, nongaussian filtering in one dimension.” 2009. Web. 04 Mar 2021.

Vancouver:

Johnson DM. The wavelet filter: a new method for nonlinear, nongaussian filtering in one dimension. [Internet] [Masters thesis]. University of Southern California; 2009. [cited 2021 Mar 04]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/172277/rec/7408.

Council of Science Editors:

Johnson DM. The wavelet filter: a new method for nonlinear, nongaussian filtering in one dimension. [Masters Thesis]. University of Southern California; 2009. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/172277/rec/7408

Kansas State University

5. Scutti, Dale. Digital implementation and parameter tuning of adaptive nonlinear differential limiters.

Degree: MS, Department of Electrical and Computer Engineering, 2016, Kansas State University

URL: http://hdl.handle.net/2097/32218

► It has been shown that the performance of communications systems can be severely limited by non-Gaussian and impulsive interference from a variety of sources. The… (more)

Subjects/Keywords: Adaptive nonlinear differential limiter; Nonlinear filtering; Digital signal processing

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APA (6^th Edition):

Scutti, D. (2016). Digital implementation and parameter tuning of adaptive nonlinear differential limiters. (Masters Thesis). Kansas State University. Retrieved from http://hdl.handle.net/2097/32218

Chicago Manual of Style (16^th Edition):

Scutti, Dale. “Digital implementation and parameter tuning of adaptive nonlinear differential limiters.” 2016. Masters Thesis, Kansas State University. Accessed March 04, 2021. http://hdl.handle.net/2097/32218.

MLA Handbook (7^th Edition):

Scutti, Dale. “Digital implementation and parameter tuning of adaptive nonlinear differential limiters.” 2016. Web. 04 Mar 2021.

Vancouver:

Scutti D. Digital implementation and parameter tuning of adaptive nonlinear differential limiters. [Internet] [Masters thesis]. Kansas State University; 2016. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/2097/32218.

Council of Science Editors:

Scutti D. Digital implementation and parameter tuning of adaptive nonlinear differential limiters. [Masters Thesis]. Kansas State University; 2016. Available from: http://hdl.handle.net/2097/32218

University of Vermont

6. Erazo, Kalil. Bayesian Filtering In Nonlinear Structural Systems With Application To Structural Health Monitoring.

Degree: PhD, Civil and Environmental Engineering, 2015, University of Vermont

URL: https://scholarworks.uvm.edu/graddis/513

► During strong earthquakes structural systems exhibit nonlinear behavior due to low-cycle fatigue, cracking, yielding and/or fracture of constituent elements. After a seismic event it… (more)

▼ During strong earthquakes structural systems exhibit nonlinear behavior due to low-cycle fatigue, cracking, yielding and/or fracture of constituent elements. After a seismic event it is essential to assess the state of damage of structures and determine if they can safely resist aftershocks or future strong motions. The current practice in post-earthquake damage assessment relies mainly on visual inspections and local testing. These approaches are limited to the ability of inspectors to reach all potentially damaged locations, and are typically intended to detect damage near the outer surfaces of the structure leaving the possibility of hidden undetected damage. Some structures in seismic prone-regions are instrumented with an array of sensors that measure their acceleration at different locations. We operate under the premise that acceleration response measurements contain information about the state of damage of structures, and it is of interest to extract this information and use it in post-earthquake damage assessment and decision making strategies. The objective of this dissertation is to show that Bayesian filters can be successfully employed to estimate the nonlinear dynamic response of instrumented structural systems. The estimated response is subsequently used for structural damage diagnosis. Bayesian filters combine dynamic response measurements at limited spatial locations with a nonlinear dynamic model to estimate the response of stochastic dynamical systems at the model degrees-of-freedom. The application of five filters is investigated: the extended, unscented and ensemble Kalman filters, the particle filter and the model-based observer. The main contributions of this dissertation are summarized as follows: i) Development of a filtering-based mechanistic damage assessment framework; ii) Experimental validation of Bayesian filters in small and large-scale structures; iii) Uncertainty quantification and propagation of response and damage estimates computed using Bayesian filters. Advisors/Committee Members: Eric M. Hernandez.

Subjects/Keywords: Bayesian filtering; Nonlinear filtering; Seismic damage; Structural health monitoring; Vibration measurements; Civil Engineering

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APA (6^th Edition):

Erazo, K. (2015). Bayesian Filtering In Nonlinear Structural Systems With Application To Structural Health Monitoring. (Doctoral Dissertation). University of Vermont. Retrieved from https://scholarworks.uvm.edu/graddis/513

Chicago Manual of Style (16^th Edition):

Erazo, Kalil. “Bayesian Filtering In Nonlinear Structural Systems With Application To Structural Health Monitoring.” 2015. Doctoral Dissertation, University of Vermont. Accessed March 04, 2021. https://scholarworks.uvm.edu/graddis/513.

MLA Handbook (7^th Edition):

Erazo, Kalil. “Bayesian Filtering In Nonlinear Structural Systems With Application To Structural Health Monitoring.” 2015. Web. 04 Mar 2021.

Vancouver:

Erazo K. Bayesian Filtering In Nonlinear Structural Systems With Application To Structural Health Monitoring. [Internet] [Doctoral dissertation]. University of Vermont; 2015. [cited 2021 Mar 04]. Available from: https://scholarworks.uvm.edu/graddis/513.

Council of Science Editors:

Erazo K. Bayesian Filtering In Nonlinear Structural Systems With Application To Structural Health Monitoring. [Doctoral Dissertation]. University of Vermont; 2015. Available from: https://scholarworks.uvm.edu/graddis/513

University of Illinois – Urbana-Champaign

7. Yang, Tao. Feedback particle filter and its applications.

Degree: PhD, 0133, 2014, University of Illinois – Urbana-Champaign

URL: http://hdl.handle.net/2142/50708

► The purpose of nonlinear filtering is to extract useful information from noisy sensor data. It finds applications in all disciplines of science and engineering, including… (more)

▼ The purpose of nonlinear filtering is to extract useful information from noisy sensor data. It finds applications in all disciplines of science and engineering, including tracking and navigation, traffic surveillance, financial engineering, neuroscience, biology, robotics, computer vision, weather forecasting, geophysical survey and oceanology, etc. This thesis is particularly concerned with the nonlinear filtering problem in the continuous-time continuous-valued state-space setting (diffusion). In this setting, the nonlinear filter is described by the Kushner-Stratonovich (K-S) stochastic partial differential equation (SPDE). For the general nonlinear non-Gaussian problem, no analytical expression for the solution of the SPDE is available. For certain special cases, finite-dimensional solution exists and one such case is the Kalman filter. The Kalman filter admits an innovation error-based feedback control structure, which is important on account of robustness, cost efficiency and ease of design, testing and operation. The limitations of Kalman filters in applications arise because of nonlinearities, not only in the signal models but also in the observation models. For such cases, Kalman filters are known to perform poorly. This motivates simulation-based methods to approximate the infinite-dimensional solution of the K-S SPDE. One popular approach is the particle filter, which is a Monte Carlo algorithm based on sequential importance sampling. Although it is potentially applicable to a general class of nonlinear non-Gaussian problems, the particle filter is known to suffer from several well-known drawbacks, such as particle degeneracy, curse of dimensionality, numerical instability and high computational cost. The goal of this dissertation is to propose a new framework for nonlinear filtering, which introduces the innovation error-based feedback control structure to the particle filter. The proposed filter is called the feedback particle filter (FPF). The first part of this dissertation covers the theory of the feedback particle filter. The filter is defined by an ensemble of controlled, stochastic, dynamic systems (the “particles”). Each particle evolves under feedback control based on its own state, and the empirical distribution of the ensemble. The feedback control law is obtained as the solution to a variational problem, in which the optimization criterion is the Kullback-Leibler divergence between the actual posterior, and the common posterior of any particle. The following conclusions are obtained for diffusions with continuous observations: 1) The optimal control solution is exact: The two posteriors match exactly, provided they are initialized with identical priors. 2) The optimal filter admits an innovation error-based gain feedback structure. 3) The optimal feedback gain is obtained via a solution of an Euler-Lagrange boundary value problem; the feedback gain equals the Kalman gain in the linear Gaussian case. The feedback particle filter offers significant variance improvements when compared to the… Advisors/Committee Members: Mehta, Prashant G. (advisor), Mehta, Prashant G. (Committee Chair), Basar, Tamer (committee member), Veeravalli, Venugopal V. (committee member), Moulin, Pierre (committee member).

Subjects/Keywords: Nonlinear filtering; estimation; particle filtering; statistical signal processing; optimal transportation; target tracking

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APA (6^th Edition):

Yang, T. (2014). Feedback particle filter and its applications. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/50708

Chicago Manual of Style (16^th Edition):

Yang, Tao. “Feedback particle filter and its applications.” 2014. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed March 04, 2021. http://hdl.handle.net/2142/50708.

MLA Handbook (7^th Edition):

Yang, Tao. “Feedback particle filter and its applications.” 2014. Web. 04 Mar 2021.

Vancouver:

Yang T. Feedback particle filter and its applications. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2014. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/2142/50708.

Council of Science Editors:

Yang T. Feedback particle filter and its applications. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2014. Available from: http://hdl.handle.net/2142/50708

University of Newcastle

8. Cea Garrido, Mauricio Esteban. Sampling and quantization in nonlinear filtering and control.

Degree: 2012, University of Newcastle

URL: http://hdl.handle.net/1959.13/935346

►

Research Doctorate - Doctor of Philosophy

The thesis describes contributions made in two areas, namely, aspects of nonlinear filtering and control over communication channels. Specifically,… (more)

▼

Research Doctorate - Doctor of Philosophy

The thesis describes contributions made in two areas, namely, aspects of nonlinear filtering and control over communication channels. Specifically, the thesis is concerned with addressing the impact of temporal and spatial quantization on the performance of estimation and control algorithms. Regarding nonlinear filtering, emphasis is placed on technical and theoretical issues regarding the impact of sampling and spatial quantization. New techniques of upsampling and downsampling are developed to address specific computational issues. Also, extensions to Lebesgue sampling are explored. In addition, a new class of nonlinear filtering algorithms, called Minimum Distortion Filters, is developed based on the use of Vector Quantization. The effectiveness of the new filtering algorithms are illustrated, by using it on a wide variety of problems including system identification, state estimation for chemical processes and radar tracking. Regarding control over communication channels, the focus is primarily on the practical problem of inner loop power control in broadband WCDMA. This control loop is characterized by the use of a one-bit-per-sample control law. This restriction severely limits the achievable performance. To address the problem, a novel adaptive quantizer is developed in the thesis. The scheme is shown to lead to significant performance improvements. The scheme has also been extended and applied to the problem of stabilizing an open loop unstable system over a bit rate constrained channel. Other control problems in WCDMA are also explored including the use of the "Happy Bit" to signal buffer sizes for the purposes of scheduling. This control loop is also subject to a one-bit-per-sample constraint. Typically, the one bit is used for a different purpose in current implementations. Here we develop an adaptive scheme based on the Happy Bit for communicating the buffer size.

Advisors/Committee Members: University of Newcastle. Faculty of Engineering & Built Environment, School of Electrical Engineering and Computer Science.

Subjects/Keywords: nonlinear filtering; quantization; sampled data; nonlinear MPC; WCDMA; networked control; constrained bit rate

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APA (6^th Edition):

Cea Garrido, M. E. (2012). Sampling and quantization in nonlinear filtering and control. (Thesis). University of Newcastle. Retrieved from http://hdl.handle.net/1959.13/935346

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Cea Garrido, Mauricio Esteban. “Sampling and quantization in nonlinear filtering and control.” 2012. Thesis, University of Newcastle. Accessed March 04, 2021. http://hdl.handle.net/1959.13/935346.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Cea Garrido, Mauricio Esteban. “Sampling and quantization in nonlinear filtering and control.” 2012. Web. 04 Mar 2021.

Vancouver:

Cea Garrido ME. Sampling and quantization in nonlinear filtering and control. [Internet] [Thesis]. University of Newcastle; 2012. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1959.13/935346.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Cea Garrido ME. Sampling and quantization in nonlinear filtering and control. [Thesis]. University of Newcastle; 2012. Available from: http://hdl.handle.net/1959.13/935346

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Mississippi State University

9. Jia, Bin. THE SPARSE-GRID BASED NONLINEAR FILTER: THEORY AND APPLICATIONS.

Degree: PhD, Aerospace Engineering, 2012, Mississippi State University

URL: http://sun.library.msstate.edu/ETD-db/theses/available/etd-03012012-152723/ ;

► Filtering or estimation is of great importance to virtually all disciplines of engineering and science that need inference, learning, information fusion, and knowledge discovery… (more)

Subjects/Keywords: Numerical Integral; Estimation; Navigation; Bayesian nonlinear filtering; Sparse-grid

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APA (6^th Edition):

Jia, B. (2012). THE SPARSE-GRID BASED NONLINEAR FILTER: THEORY AND APPLICATIONS. (Doctoral Dissertation). Mississippi State University. Retrieved from http://sun.library.msstate.edu/ETD-db/theses/available/etd-03012012-152723/ ;

Chicago Manual of Style (16^th Edition):

Jia, Bin. “THE SPARSE-GRID BASED NONLINEAR FILTER: THEORY AND APPLICATIONS.” 2012. Doctoral Dissertation, Mississippi State University. Accessed March 04, 2021. http://sun.library.msstate.edu/ETD-db/theses/available/etd-03012012-152723/ ;.

MLA Handbook (7^th Edition):

Jia, Bin. “THE SPARSE-GRID BASED NONLINEAR FILTER: THEORY AND APPLICATIONS.” 2012. Web. 04 Mar 2021.

Vancouver:

Jia B. THE SPARSE-GRID BASED NONLINEAR FILTER: THEORY AND APPLICATIONS. [Internet] [Doctoral dissertation]. Mississippi State University; 2012. [cited 2021 Mar 04]. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-03012012-152723/ ;.

Council of Science Editors:

Jia B. THE SPARSE-GRID BASED NONLINEAR FILTER: THEORY AND APPLICATIONS. [Doctoral Dissertation]. Mississippi State University; 2012. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-03012012-152723/ ;

University of Georgia

10. Lyubimov, Konstantin. Valuation of residential mortgage default and prepayment under stochastic house prices.

Degree: 2014, University of Georgia

URL: http://hdl.handle.net/10724/26392

► This dissertation applies a valuation model for residential mortgages subject to exogenously specified conditional probabilities of prepayment and default to data on subprime and Alt-A… (more)

Subjects/Keywords: doubly stochastic; default; prepayment; latent factor; nonlinear filtering; mortgage valuation

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APA (6^th Edition):

Lyubimov, K. (2014). Valuation of residential mortgage default and prepayment under stochastic house prices. (Thesis). University of Georgia. Retrieved from http://hdl.handle.net/10724/26392

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Lyubimov, Konstantin. “Valuation of residential mortgage default and prepayment under stochastic house prices.” 2014. Thesis, University of Georgia. Accessed March 04, 2021. http://hdl.handle.net/10724/26392.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Lyubimov, Konstantin. “Valuation of residential mortgage default and prepayment under stochastic house prices.” 2014. Web. 04 Mar 2021.

Vancouver:

Lyubimov K. Valuation of residential mortgage default and prepayment under stochastic house prices. [Internet] [Thesis]. University of Georgia; 2014. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10724/26392.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lyubimov K. Valuation of residential mortgage default and prepayment under stochastic house prices. [Thesis]. University of Georgia; 2014. Available from: http://hdl.handle.net/10724/26392

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Texas A&M University

11. Weisman, Ryan Michael 1984-. Nonlinear Transformations and Filtering Theory for Space Operations.

Degree: PhD, Aerospace Engineering, 2012, Texas A&M University

URL: http://hdl.handle.net/1969.1/148211

► Decisions for asset allocation and protection are predicated upon accurate knowledge of the current operating environment as well as correctly characterizing the evolution of the… (more)

▼ Decisions for asset allocation and protection are predicated upon accurate knowledge of the current operating environment as well as correctly characterizing the evolution of the environment over time. The desired kinematic and kinetic states of objects in question cannot be measured directly in most cases and instead are inferred or estimated from available measurements using a filtering process. Often, nonlinear transformations between the measurement domain and desired state domain distort the state domain probability density function yielding a form which does not necessarily resemble the form assumed in the filtering algorithm. The distortion effect must be understood in greater detail and appropriately accounted for so that even if sensors, state estimation algorithms, and state propagation algorithms operate in different domains, they can all be effectively utilized without any information loss due to domain transformations. This research presents an analytical investigation into understanding how non-linear transformations of stochastic, but characterizable, processes affect state and uncertainty estimation with direct application to space object surveillance and space- craft attitude determination. Analysis is performed with attention to construction of the state domain probability density function since state uncertainty and correlation are derived from the statistical moments of the probability density function. Analytical characterization of the effect nonlinear transformations impart on the structure of state probability density functions has direct application to conventional non- linear filtering and propagation algorithms in three areas: (1) understanding how smoothing algorithms used to estimate indirectly observed states impact state uncertainty, (2) justification or refutation of assumed state uncertainty distribution for more realistic uncertainty quantification, and (3) analytic automation of initial state estimate and covariance in lieu of user tuning. A nonlinear filtering algorithm based upon Bayes’ Theorem is presented to ac- count for the impact nonlinear domain transformations impart on probability density functions during the measurement update and propagation phases. The algorithm is able to accommodate different combinations of sensors for state estimation which can also be used to hypothesize system parameters or unknown states from available measurements because information is able to appropriately accounted for. Advisors/Committee Members: Alfriend, Kyle T (advisor), Valasek, John (advisor), Turner, James D (committee member), Parlos, Alexander G (committee member).

Subjects/Keywords: filter initialization; uncertainty estimation; bayesian filtering; nonlinear estimation; space surveillance

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APA (6^th Edition):

Weisman, R. M. 1. (2012). Nonlinear Transformations and Filtering Theory for Space Operations. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/148211

Chicago Manual of Style (16^th Edition):

Weisman, Ryan Michael 1984-. “Nonlinear Transformations and Filtering Theory for Space Operations.” 2012. Doctoral Dissertation, Texas A&M University. Accessed March 04, 2021. http://hdl.handle.net/1969.1/148211.

MLA Handbook (7^th Edition):

Weisman, Ryan Michael 1984-. “Nonlinear Transformations and Filtering Theory for Space Operations.” 2012. Web. 04 Mar 2021.

Vancouver:

Weisman RM1. Nonlinear Transformations and Filtering Theory for Space Operations. [Internet] [Doctoral dissertation]. Texas A&M University; 2012. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1969.1/148211.

Council of Science Editors:

Weisman RM1. Nonlinear Transformations and Filtering Theory for Space Operations. [Doctoral Dissertation]. Texas A&M University; 2012. Available from: http://hdl.handle.net/1969.1/148211

University of Illinois – Urbana-Champaign

12. Medarametla, Krishna Kalyan. Comparison of two nonlinear filtering techniques - the extended Kalman filter and the feedback particle filter.

Degree: MS, 0133, 2014, University of Illinois – Urbana-Champaign

URL: http://hdl.handle.net/2142/50584

► In a recent work it has been shown that importance sampling can be avoided in particle filter through an innovation structure inspired by traditional nonlinear… (more)

Subjects/Keywords: Extended Kalman filter; Feedback particle filter; Comparison; Nonlinear filtering

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APA (6^th Edition):

Medarametla, K. K. (2014). Comparison of two nonlinear filtering techniques - the extended Kalman filter and the feedback particle filter. (Thesis). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/50584

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Medarametla, Krishna Kalyan. “Comparison of two nonlinear filtering techniques - the extended Kalman filter and the feedback particle filter.” 2014. Thesis, University of Illinois – Urbana-Champaign. Accessed March 04, 2021. http://hdl.handle.net/2142/50584.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Medarametla, Krishna Kalyan. “Comparison of two nonlinear filtering techniques - the extended Kalman filter and the feedback particle filter.” 2014. Web. 04 Mar 2021.

Vancouver:

Medarametla KK. Comparison of two nonlinear filtering techniques - the extended Kalman filter and the feedback particle filter. [Internet] [Thesis]. University of Illinois – Urbana-Champaign; 2014. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/2142/50584.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Medarametla KK. Comparison of two nonlinear filtering techniques - the extended Kalman filter and the feedback particle filter. [Thesis]. University of Illinois – Urbana-Champaign; 2014. Available from: http://hdl.handle.net/2142/50584

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of Tennessee – Knoxville

13. Pan, Xiaoyang. Asymptotics for dynamical systems driven by jump noise.

Degree: 2018, University of Tennessee – Knoxville

URL: https://trace.tennessee.edu/utk_graddiss/5065

► This dissertation studies asymptotic estimates for dynamical systems with jumps. We first focus on the parameter estimation problem for a linear partially observed system. A… (more)

Subjects/Keywords: Partially observed system; Jump noise; Large and moderate deviations; Nonlinear filtering

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

APA (6^th Edition):

Pan, X. (2018). Asymptotics for dynamical systems driven by jump noise. (Doctoral Dissertation). University of Tennessee – Knoxville. Retrieved from https://trace.tennessee.edu/utk_graddiss/5065

Chicago Manual of Style (16^th Edition):

Pan, Xiaoyang. “Asymptotics for dynamical systems driven by jump noise.” 2018. Doctoral Dissertation, University of Tennessee – Knoxville. Accessed March 04, 2021. https://trace.tennessee.edu/utk_graddiss/5065.

MLA Handbook (7^th Edition):

Pan, Xiaoyang. “Asymptotics for dynamical systems driven by jump noise.” 2018. Web. 04 Mar 2021.

Vancouver:

Pan X. Asymptotics for dynamical systems driven by jump noise. [Internet] [Doctoral dissertation]. University of Tennessee – Knoxville; 2018. [cited 2021 Mar 04]. Available from: https://trace.tennessee.edu/utk_graddiss/5065.

Council of Science Editors:

Pan X. Asymptotics for dynamical systems driven by jump noise. [Doctoral Dissertation]. University of Tennessee – Knoxville; 2018. Available from: https://trace.tennessee.edu/utk_graddiss/5065

Michigan State University

14. Boker, Almuatazbellah Muftah. Estimation and control of nonlinear systems using extended high-gain observers.

Degree: 2013, Michigan State University

URL: http://etd.lib.msu.edu/islandora/object/etd:2275

►

Thesis Ph. D. Michigan State University. Electrical Engineering 2013.

Providing accurate state estimation is important for many systems. This is especially the case for systems… (more)

▼

Thesis Ph. D. Michigan State University. Electrical Engineering 2013.

Providing accurate state estimation is important for many systems. This is especially the case for systems whose states may be very difficult or even impossible to measure or require expensive or unreliable sensors. From another prospective, making all the states available simplifies considerably the control design and helps in providing practical and economic solutions to many control problems. The first part of our work involves the design of an observer for a class of nonlinear systems that can potentially admit unstable zero dynamics. The structure of the observer is com-posed of an Extended High-Gain Observer (EHGO), for the estimation of the derivatives of the output, augmented with an Extended Kalman Filter for the estimation of the states of the internaldynamics. The EHGO is also utilized to estimate a signal that is used as a virtual output to an auxiliary system comprised of the internal dynamics. We demonstrate the efficacy of the observer in two examples; namely, a synchronous generator connected to an infinite bus and a Translating Oscillator with a Rotating Actuator (TORA) system.In the special case of the system being linear in the states of the internal dynamics, we achieve semi-global asymptotic convergence of the estimation error. We also solve for this class of systems, which may have unstable zero dynamics, the problem of output feedback stabilization. We allow the use of any globally stabilizing full state feedback control scheme. We then recover its performance using an observer-based output feedback control. As a demonstration of the efficacy of this control scheme, we design an output feedback stabilizing control for the DC-to-DC boost converter system.We also consider the problem of output feedback tracking of possibly non-minimum phase nonlinear systems where the internal dynamics have a full relative degree with respect to a virtual output. In this case, the internal dynamics can be represented in the chain-of-integrators form. This allows the use of a high-gain observer to estimate the states of the internal dynamics, and hence, making all the system states available for the controller. We allow the use of any globally stabilizing full state feedback control and we show that it is possible to recover its stability properties and trajectory performance. Finally, as a demonstration of the design procedure, we solve the problem of output feedback tracking control of flexible joint manipulators where the link angle is the output to be controlled and the motor angle is the measured output. We demonstrate the effectiveness of the proposed scheme in the single link case, and where the zero dynamics are not asymptotically stable.

Description based on online resource; title from PDF t.p. (viewed on Sept. 10, 2014)

Advisors/Committee Members: Khalil, Hassan K, Tan, Xiaobo, Zhu, Guoming, Mukherjee, Ranjan.

Subjects/Keywords: Nonlinear systems; Estimation theory; Control theory; Kalman filtering; Electrical engineering

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

APA (6^th Edition):

Boker, A. M. (2013). Estimation and control of nonlinear systems using extended high-gain observers. (Thesis). Michigan State University. Retrieved from http://etd.lib.msu.edu/islandora/object/etd:2275

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Boker, Almuatazbellah Muftah. “Estimation and control of nonlinear systems using extended high-gain observers.” 2013. Thesis, Michigan State University. Accessed March 04, 2021. http://etd.lib.msu.edu/islandora/object/etd:2275.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Boker, Almuatazbellah Muftah. “Estimation and control of nonlinear systems using extended high-gain observers.” 2013. Web. 04 Mar 2021.

Vancouver:

Boker AM. Estimation and control of nonlinear systems using extended high-gain observers. [Internet] [Thesis]. Michigan State University; 2013. [cited 2021 Mar 04]. Available from: http://etd.lib.msu.edu/islandora/object/etd:2275.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Boker AM. Estimation and control of nonlinear systems using extended high-gain observers. [Thesis]. Michigan State University; 2013. Available from: http://etd.lib.msu.edu/islandora/object/etd:2275

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

15. Liu, Kun-Chu. Model-based failure detection in induction motors using nonlinear filtering.

Degree: PhD, Systems and Control Engineering, 1995, Case Western Reserve University School of Graduate Studies

URL: http://rave.ohiolink.edu/etdc/view?acc_num=case1058279752

► In this dissertation, we present a model-based failure detection method for induction motors. Our method addresses two failure modes of the squirrel-cage induction motors; namely,… (more)

Subjects/Keywords: Induction motors; Nonlinear filtering

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APA (6^th Edition):

Liu, K. (1995). Model-based failure detection in induction motors using nonlinear filtering. (Doctoral Dissertation). Case Western Reserve University School of Graduate Studies. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=case1058279752

Chicago Manual of Style (16^th Edition):

Liu, Kun-Chu. “Model-based failure detection in induction motors using nonlinear filtering.” 1995. Doctoral Dissertation, Case Western Reserve University School of Graduate Studies. Accessed March 04, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=case1058279752.

MLA Handbook (7^th Edition):

Liu, Kun-Chu. “Model-based failure detection in induction motors using nonlinear filtering.” 1995. Web. 04 Mar 2021.

Vancouver:

Liu K. Model-based failure detection in induction motors using nonlinear filtering. [Internet] [Doctoral dissertation]. Case Western Reserve University School of Graduate Studies; 1995. [cited 2021 Mar 04]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1058279752.

Council of Science Editors:

Liu K. Model-based failure detection in induction motors using nonlinear filtering. [Doctoral Dissertation]. Case Western Reserve University School of Graduate Studies; 1995. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1058279752

Virginia Tech

16. Netto, Marcos. Robust Identification, Estimation, and Control of Electric Power Systems using the Koopman Operator-Theoretic Framework.

Degree: PhD, Electrical Engineering, 2019, Virginia Tech

URL: http://hdl.handle.net/10919/87728

► Electric power systems are complex, large-scale, and given the bidirectional causality between economic growth and electricity consumption, they are constantly being expanded. In the U.S.,… (more)

▼ Electric power systems are complex, large-scale, and given the bidirectional causality between economic growth and electricity consumption, they are constantly being expanded. In the U.S., some of the electric power grid facilities date back to the 1880s, and this aging system is operating at its capacity limits. In addition, the international pressure for sustainability is driving an unprecedented deployment of renewable energy sources into the grid. Unlike the case of other primary sources of electric energy such as coal and nuclear, the electricity generated from renewable energy sources is strongly influenced by the weather conditions, which are very challenging to forecast even for short periods of time. Within this context, the mathematical models that have aided engineers to design and operate electric power grids over the past decades are falling short when uncertainties are incorporated to the models of such high-dimensional systems. Consequently, researchers are investigating alternative data-driven approaches. This is not only motivated by the need to overcome the above challenges, but it is also fueled by the increasing amount of data produced by today’s powerful computational resources and experimental apparatus. In power systems, a massive amount of data will be available thanks to the deployment of measuring devices called phasor measurement units. Along these lines, the Koopman operator theory is a promising framework for the integration of data analysis into our mathematical knowledge, and is bringing an exciting perspective on the treatment of high-dimensional systems that lie in the forefront of science and technology. In the research work reported in this dissertation, the Koopman operator theory has been exploited to seek for solutions to some of the challenges that are threatening the safe, reliable, and efficient operation of electric power systems. Advisors/Committee Members: Mili, Lamine M. (committeechair), von Spakovsky, Michael R. (committee member), Stilwell, Daniel J. (committee member), Susuki, Yoshihiko (committee member), Kekatos, Vasileios (committee member), Centeno, Virgilio A. (committee member).

Subjects/Keywords: Dynamical systems; Kalman filtering; Koopman operator; Koopman mode decomposition; modal analysis; nonlinear identification; nonlinear dynamics; participation factors; robust estimation and filtering; power system stability and control

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APA (6^th Edition):

Netto, M. (2019). Robust Identification, Estimation, and Control of Electric Power Systems using the Koopman Operator-Theoretic Framework. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/87728

Chicago Manual of Style (16^th Edition):

Netto, Marcos. “Robust Identification, Estimation, and Control of Electric Power Systems using the Koopman Operator-Theoretic Framework.” 2019. Doctoral Dissertation, Virginia Tech. Accessed March 04, 2021. http://hdl.handle.net/10919/87728.

MLA Handbook (7^th Edition):

Netto, Marcos. “Robust Identification, Estimation, and Control of Electric Power Systems using the Koopman Operator-Theoretic Framework.” 2019. Web. 04 Mar 2021.

Vancouver:

Netto M. Robust Identification, Estimation, and Control of Electric Power Systems using the Koopman Operator-Theoretic Framework. [Internet] [Doctoral dissertation]. Virginia Tech; 2019. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/10919/87728.

Council of Science Editors:

Netto M. Robust Identification, Estimation, and Control of Electric Power Systems using the Koopman Operator-Theoretic Framework. [Doctoral Dissertation]. Virginia Tech; 2019. Available from: http://hdl.handle.net/10919/87728

University of Alberta

17. Xu, Ning. Nonlinear control of a voltage source converter.

Degree: MS, Department of Electrical and Computer Engineering, 2010, University of Alberta

URL: https://era.library.ualberta.ca/files/1r66j1174

► Due to its unique features such as controllable power factor, controllable bi-directional power flow, and rapid dynamic response, Voltage Source Converters (VSCs) have been widely… (more)

Subjects/Keywords: voltage source converter; experimental verification; active filtering; nonlinear control; power factor control

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APA (6^th Edition):

Xu, N. (2010). Nonlinear control of a voltage source converter. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/1r66j1174

Chicago Manual of Style (16^th Edition):

Xu, Ning. “Nonlinear control of a voltage source converter.” 2010. Masters Thesis, University of Alberta. Accessed March 04, 2021. https://era.library.ualberta.ca/files/1r66j1174.

MLA Handbook (7^th Edition):

Xu, Ning. “Nonlinear control of a voltage source converter.” 2010. Web. 04 Mar 2021.

Vancouver:

Xu N. Nonlinear control of a voltage source converter. [Internet] [Masters thesis]. University of Alberta; 2010. [cited 2021 Mar 04]. Available from: https://era.library.ualberta.ca/files/1r66j1174.

Council of Science Editors:

Xu N. Nonlinear control of a voltage source converter. [Masters Thesis]. University of Alberta; 2010. Available from: https://era.library.ualberta.ca/files/1r66j1174

Penn State University

18. Hussain, Magni Stentoft. Adaptive Digital Filtering Using the Bio-Inspired Firefly Algorithm.

Degree: 2019, Penn State University

URL: https://submit-etda.libraries.psu.edu/catalog/17117msh5334

► In recent literature, bio-inspired optimization algorithms have been shown to perform well in IIR and nonlinear applications. A relatively new bio-inspired optimization algorithm, the Firefly… (more)

▼ In recent literature, bio-inspired optimization algorithms have been shown to perform well in IIR and nonlinear applications. A relatively new bio-inspired optimization algorithm, the Firefly Algorithm, has shown positive results in other engineering applications, but its application to adaptive filtering is relatively scarce. In this thesis, the performance of the Firefly Algorithm, with use of a Lévy flights random step, is analyzed in the following adaptive filtering applications: 1) IIR system identification, 2) nonlinear system identification, and 3) fetal electrocardiogram adaptive noise cancellation. In several IIR system identification experiments, the Firefly Algorithm is shown to have notably better performance than the Genetic Algorithm and the Particle Swarm Optimization Algorithm, both in convergence rate and error value at convergence. Several IIR filter form experiments using the Firefly Algorithm also show the cascade-form adaptive filter having the most consistently-good performance, although it is seen in general the Firefly Algorithm can adapt direct, cascade, and parallel form IIR adaptive filters sufficiently well. In nonlinear system identification, the Firefly Algorithm, while shown to not converge as quickly as the Genetic Algorithm, the Particle Swarm Optimization Algorithm and the Modified Particle Swarm Optimization Algorithm, is shown to converge to lower error values than the aforementioned algorithms. Lastly, in adaptive noise cancelling of maternal signals from fetal electrocardiograms, the Firefly Algorithm, applied to an adaptive IIR filter, is seen to provide better performance over the LMS Algorithm, applied to an FIR adaptive filter, when using the same number of adaptable parameters. Future work is planned for investigating the performance of the Firefly Algorithm applied to coupled-form IIR adaptive filters. Advisors/Committee Members: W. Kenneth Jenkins, Thesis Advisor/Co-Advisor, John F. Doherty, Thesis Advisor/Co-Advisor, Kultegin Aydin, Program Head/Chair.

Subjects/Keywords: Adaptive Filtering; Firefly Algorithm; IIR Filter; Nonlinear Filter; System Identification; Fetal Electrocardiogram; Adaptive Noise Cancelling

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APA (6^th Edition):

Hussain, M. S. (2019). Adaptive Digital Filtering Using the Bio-Inspired Firefly Algorithm. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/17117msh5334

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Hussain, Magni Stentoft. “Adaptive Digital Filtering Using the Bio-Inspired Firefly Algorithm.” 2019. Thesis, Penn State University. Accessed March 04, 2021. https://submit-etda.libraries.psu.edu/catalog/17117msh5334.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Hussain, Magni Stentoft. “Adaptive Digital Filtering Using the Bio-Inspired Firefly Algorithm.” 2019. Web. 04 Mar 2021.

Vancouver:

Hussain MS. Adaptive Digital Filtering Using the Bio-Inspired Firefly Algorithm. [Internet] [Thesis]. Penn State University; 2019. [cited 2021 Mar 04]. Available from: https://submit-etda.libraries.psu.edu/catalog/17117msh5334.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Hussain MS. Adaptive Digital Filtering Using the Bio-Inspired Firefly Algorithm. [Thesis]. Penn State University; 2019. Available from: https://submit-etda.libraries.psu.edu/catalog/17117msh5334

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Syracuse University

19. Leskiw, Donald. The Extended Preferred Ordering Theorem for Radar Tracking Using the Extended Kalman Filter.

Degree: PhD, Electrical Engineering and Computer Science, 2011, Syracuse University

URL: https://surface.syr.edu/eecs_etd/315

► A certain problem in nonlinear estimation exists in radar tracking. Usually radar detections provide instantaneous position measurements in radar (polar) coordinates at discrete times,… (more)

Subjects/Keywords: alman Filtering; Nonlinear Estimation; Preferred Ordering; Radar Tracking; Electrical and Computer Engineering

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APA (6^th Edition):

Leskiw, D. (2011). The Extended Preferred Ordering Theorem for Radar Tracking Using the Extended Kalman Filter. (Doctoral Dissertation). Syracuse University. Retrieved from https://surface.syr.edu/eecs_etd/315

Chicago Manual of Style (16^th Edition):

Leskiw, Donald. “The Extended Preferred Ordering Theorem for Radar Tracking Using the Extended Kalman Filter.” 2011. Doctoral Dissertation, Syracuse University. Accessed March 04, 2021. https://surface.syr.edu/eecs_etd/315.

MLA Handbook (7^th Edition):

Leskiw, Donald. “The Extended Preferred Ordering Theorem for Radar Tracking Using the Extended Kalman Filter.” 2011. Web. 04 Mar 2021.

Vancouver:

Leskiw D. The Extended Preferred Ordering Theorem for Radar Tracking Using the Extended Kalman Filter. [Internet] [Doctoral dissertation]. Syracuse University; 2011. [cited 2021 Mar 04]. Available from: https://surface.syr.edu/eecs_etd/315.

Council of Science Editors:

Leskiw D. The Extended Preferred Ordering Theorem for Radar Tracking Using the Extended Kalman Filter. [Doctoral Dissertation]. Syracuse University; 2011. Available from: https://surface.syr.edu/eecs_etd/315

University of Minnesota

20. Du, Juan. Dynamic Imaging of Tissue Perfusion Using Ultrasound Contrast Agents.

Degree: PhD, Electrical/Computer Engineering, 2016, University of Minnesota

URL: http://hdl.handle.net/11299/183381

► Tissue perfusion is an important indicator of the health and vitality of organs such as liver and kidney. Imaging tissue perfusion has significant clinical applications… (more)

▼ Tissue perfusion is an important indicator of the health and vitality of organs such as liver and kidney. Imaging tissue perfusion has significant clinical applications such as myocardial infarction. Contrast-enhanced ultrasound (CEUS) has been clinically used in imaging myocardial perfusion since the 1990s. It was realized, however, that standard B-mode imaging did not have the specificity required to image tissue perfusion in other clinical applications, e.g. tumor perfusion. Microbubble ultrasound contrast agents (UCA) composed of an elastic shell and inert gas content are able to generate nonlinear harmonics. Therefore, nonlinear methods such as harmonic, subharmonic and multipulse imaging were proposed to improve the sensitivity and specificity of perfusion imaging. In this dissertation, a novel method to image the nonlinear response of UCA is investigated by extracting the signal using an adaptive third-order Volterra filter (TVF). Unlike harmonic and sub-harmonic imaging methods, the TVF separates the linear, quadratic and cubic components from the beamformed pulse-echo data to capture polynomial nonlinearities throughout the system bandwidth. This allows for imaging using broadband pulse transmission to preserve the axial resolution and the signal to noise ratio (SNR). In addition, the quadratic and cubic kernels of the TVF inherently suppress additive Gaussian noise, which lowers the noise floor and improves the detection of UCA activity in low-perfusion regions. Results from in vitro and in vivo imaging experiments have demonstrated the significance of the advantage of the post-beamforming VF in imaging UCA activity. Under microflow conditions (as in blood microcirculation), the echogenicity of the UCA microbubbles exhibit temporal dynamics different from the surrounding tissue. For example, the temporal variance of the echogenicity in the presence of UCA is typically higher than that of the same tissue in the absence of UCA. We introduced the temporal perfusion index (TPI) to capture UCA dynamic activity under microflow conditions. The TPI is a spatial measurement that rewards temporal variance at a given image pixel and penalizes the average image intensity over a small spatial mask. An appropriate selection of dynamic range reduces the sensitivity of the TPI to noise and improves the specificity to temporal contrast variations. This approach for finding the "threshold dynamic range" is extended to account for the breathing motion when the method is applied to in vivo data. The VF and TPI methods were applied to a variety of data sets collected from in vitro and in vivo imaging targets. These include micro channels embedded in tissue-mimicking phantoms, subcutaneous tumors in vivo and brain tissue in vivo with and without UCA. The results clearly demonstrate the advantages of the proposed methods in imaging UCA activity under microflow conditions and show the way towards quantitative noninvasive perfusion imaging using pulse-echo ultrasound.

Subjects/Keywords: Dynamic imaging; Nonlinear filtering; Quantitative perfusion imaging; Tissue perfusion; Ultrasound contrast agent

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

APA (6^th Edition):

Du, J. (2016). Dynamic Imaging of Tissue Perfusion Using Ultrasound Contrast Agents. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/183381

Chicago Manual of Style (16^th Edition):

Du, Juan. “Dynamic Imaging of Tissue Perfusion Using Ultrasound Contrast Agents.” 2016. Doctoral Dissertation, University of Minnesota. Accessed March 04, 2021. http://hdl.handle.net/11299/183381.

MLA Handbook (7^th Edition):

Du, Juan. “Dynamic Imaging of Tissue Perfusion Using Ultrasound Contrast Agents.” 2016. Web. 04 Mar 2021.

Vancouver:

Du J. Dynamic Imaging of Tissue Perfusion Using Ultrasound Contrast Agents. [Internet] [Doctoral dissertation]. University of Minnesota; 2016. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/11299/183381.

Council of Science Editors:

Du J. Dynamic Imaging of Tissue Perfusion Using Ultrasound Contrast Agents. [Doctoral Dissertation]. University of Minnesota; 2016. Available from: http://hdl.handle.net/11299/183381

Brunel University

21. Alqaralleh, Huthaifa Sameeh. Modelling house price cycles in large metropolitan areas.

Degree: PhD, 2017, Brunel University

URL: http://bura.brunel.ac.uk/handle/2438/15892 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.764881

► The volatility of house prices can raise systemic risks in the housing market due to the vulnerability of the banking and mortgage sectors to such… (more)

▼ The volatility of house prices can raise systemic risks in the housing market due to the vulnerability of the banking and mortgage sectors to such fluctuations. Moreover, the extreme increases in housing markets have been considered a key feature of the last economic crisis and the run-up to it. Such increases, however, came to a sudden halt immediately before the crisis or directly it began. Despite the recent growth of scholarly work on the role of house price behaviour in economic stability, fundamental questions have yet to be answered: for instance: (i) how far do the nonlinear models outperform the linear models? And how does such nonlinearity explain the asymmetry in the cycle; (ii) what are the main characteristics of house price cycles, and how do they differ over time; and (iii) what kind of policy intervention would stop a real estate boom? This thesis, made up of three empirical essays, aims to take a step forward in answering these questions. The first essay examines whether house prices in large metropolitan areas such as London, New York and Hong Kong follow linear or nonlinear models. The Smooth Transition Autoregressive model was used on a sample of monthly data over the period 1996:1 to 2015:12. The results indicate that linear models are unsuitable for modelling the housing market for the chosen cities. Moreover, strong evidence indicates that real estate prices are largely nonlinear and can well be modelled using a logistic smooth transition model (LSTAR). Estimation results also show different degrees of asymmetry. In particular, the speed of transition between the expansion and contraction of house prices is greater in London than it is in Hong Kong while the speed of transition between boom and bust in New York house prices is the slowest. Further, the forecast results suggest that the LSTAR outdoes the linear model in out-of-sample performance. The second essay investigates the main features of house price cycles in the same major metropolitan areas by providing a reasonable level of discrimination between the cyclical decomposition techniques available for capturing suitable measurements for house price cycles. Through a sample of large cities in several countries, it is shown that the model-based filter is suitable for capturing the main features of house price cycles and the results confirm that these cycles are centred at low frequency. Moreover, there is evidence of substantial variation in the duration and amplitude of these cycles both across cities and over time. The third essay provides evidence that real house prices are significantly affected by financial stability policies. Considering the Hong Kong experience, the results show strong evidence of duration dependences in both the upswing and downswing phases of the cycle. Moreover, the time taken to reach the turning point increases dramatically as the cycle proceeds. The findings also suggest that there is feedback between house price volatility and the policies that affect the housing market. Accordingly, house prices respond with…

Subjects/Keywords: 330.01; Nonlinear modelling; Filtering techniques; Macro-prudential policy; Asymmetric volatility; Survival model

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APA (6^th Edition):

Alqaralleh, H. S. (2017). Modelling house price cycles in large metropolitan areas. (Doctoral Dissertation). Brunel University. Retrieved from http://bura.brunel.ac.uk/handle/2438/15892 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.764881

Chicago Manual of Style (16^th Edition):

Alqaralleh, Huthaifa Sameeh. “Modelling house price cycles in large metropolitan areas.” 2017. Doctoral Dissertation, Brunel University. Accessed March 04, 2021. http://bura.brunel.ac.uk/handle/2438/15892 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.764881.

MLA Handbook (7^th Edition):

Alqaralleh, Huthaifa Sameeh. “Modelling house price cycles in large metropolitan areas.” 2017. Web. 04 Mar 2021.

Vancouver:

Alqaralleh HS. Modelling house price cycles in large metropolitan areas. [Internet] [Doctoral dissertation]. Brunel University; 2017. [cited 2021 Mar 04]. Available from: http://bura.brunel.ac.uk/handle/2438/15892 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.764881.

Council of Science Editors:

Alqaralleh HS. Modelling house price cycles in large metropolitan areas. [Doctoral Dissertation]. Brunel University; 2017. Available from: http://bura.brunel.ac.uk/handle/2438/15892 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.764881

Indian Institute of Science

22. Radhika, Bayya. Monte Carlo Simulation Based Response Estimation and Model Updating in Nonlinear Random Vibrations.

Degree: PhD, Faculty of Engineering, 2018, Indian Institute of Science

URL: http://etd.iisc.ac.in/handle/2005/3162

► The study of randomly excited nonlinear dynamical systems forms the focus of this thesis. We discuss two classes of problems: first, the characterization of nonlinear… (more)

▼ The study of randomly excited nonlinear dynamical systems forms the focus of this thesis. We discuss two classes of problems: first, the characterization of nonlinear random response of the system before it comes into existence and, the second, assimilation of measured responses into the mathematical model of the system after the system comes into existence. The first class of problems constitutes forward problems while the latter belongs to the class of inverse problems. An outstanding feature of these problems is that they are almost always not amenable for exact solutions. We tackle in the present study these two classes of problems using Monte Carlo simulation tools in conjunction with Markov process theory, Bayesian model updating strategies, and particle filtering based dynamic state estimation methods. It is well recognized in literature that any successful application of Monte Carlo simulation methods to practical problems requires the simulation methods to be reinforced with effective means of controlling sampling variance. This can be achieved by incorporating any problem specific qualitative and (or) quantitative information that one might have about system behavior in formulating estimators for response quantities of interest. In the present thesis we outline two such approaches for variance reduction. The first of these approaches employs a substructuring scheme, which partitions the system states into two sets such that the probability distribution of the states in one of the sets conditioned on the other set become amenable for exact analytical solution. In the second approach, results from data based asymptotic extreme value analysis are employed to tackle problems of time variant reliability analysis and updating of this reliability. We exemplify in this thesis the proposed approaches for response estimation and model updating by considering wide ranging problems of interest in structural engineering, namely, nonlinear response and reliability analyses under stationary and (or) nonstationary random excitations, response sensitivity model updating, force identification, residual displacement analysis in instrumented inelastic structures under transient excitations, problems of dynamic state estimation in systems with local nonlinearities, and time variant reliability analysis and reliability model updating. We have organized the thesis into eight chapters and three appendices. A resume of contents of these chapters and appendices follows. In the first chapter we aim to provide an overview of mathematical tools which form the basis for investigations reported in the thesis. The starting point of the study is taken to be a set of coupled stochastic differential equations, which are obtained after discretizing spatial variables, typically, based on application of finite element methods. Accordingly, we provide a summary of the following topics: (a) Markov vector approach for characterizing time evolution of transition probability density functions, which includes the forward and backward Kolmogorov… Advisors/Committee Members: Manohar, C S (advisor).

Subjects/Keywords: Nonlienar Random Vibrations; Monte Carlo Simulation Methods; Kalman-SIS Filtering; Structural Dynamics; Nonlinear Dynamical Systems; Asymptotic Extreme Value Theory; Nonlinear Systems - Dynamic State Estimation; Kalman-SIS Filter; Kalman and SIS Filtering; Nonlinear Vibrating Structures; Asymptotic Extreme Value Analysis; Civil Engineering

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

APA (6^th Edition):

Radhika, B. (2018). Monte Carlo Simulation Based Response Estimation and Model Updating in Nonlinear Random Vibrations. (Doctoral Dissertation). Indian Institute of Science. Retrieved from http://etd.iisc.ac.in/handle/2005/3162

Chicago Manual of Style (16^th Edition):

Radhika, Bayya. “Monte Carlo Simulation Based Response Estimation and Model Updating in Nonlinear Random Vibrations.” 2018. Doctoral Dissertation, Indian Institute of Science. Accessed March 04, 2021. http://etd.iisc.ac.in/handle/2005/3162.

MLA Handbook (7^th Edition):

Radhika, Bayya. “Monte Carlo Simulation Based Response Estimation and Model Updating in Nonlinear Random Vibrations.” 2018. Web. 04 Mar 2021.

Vancouver:

Radhika B. Monte Carlo Simulation Based Response Estimation and Model Updating in Nonlinear Random Vibrations. [Internet] [Doctoral dissertation]. Indian Institute of Science; 2018. [cited 2021 Mar 04]. Available from: http://etd.iisc.ac.in/handle/2005/3162.

Council of Science Editors:

Radhika B. Monte Carlo Simulation Based Response Estimation and Model Updating in Nonlinear Random Vibrations. [Doctoral Dissertation]. Indian Institute of Science; 2018. Available from: http://etd.iisc.ac.in/handle/2005/3162

Queensland University of Technology

23. McClelland, Andrew James. Self excitation in equity indices.

Degree: 2012, Queensland University of Technology

URL: https://eprints.qut.edu.au/63629/

► A "self-exciting" market is one in which the probability of observing a crash increases in response to the occurrence of a crash. It essentially describes… (more)

Subjects/Keywords: self exciting; option implied; transform-based option pricing; affine jump diffusion; market crash; particle filtering; nonlinear filtering; risk premia; parallelisation; graphics processing unit

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APA (6^th Edition):

McClelland, A. J. (2012). Self excitation in equity indices. (Thesis). Queensland University of Technology. Retrieved from https://eprints.qut.edu.au/63629/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

McClelland, Andrew James. “Self excitation in equity indices.” 2012. Thesis, Queensland University of Technology. Accessed March 04, 2021. https://eprints.qut.edu.au/63629/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

McClelland, Andrew James. “Self excitation in equity indices.” 2012. Web. 04 Mar 2021.

Vancouver:

McClelland AJ. Self excitation in equity indices. [Internet] [Thesis]. Queensland University of Technology; 2012. [cited 2021 Mar 04]. Available from: https://eprints.qut.edu.au/63629/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

McClelland AJ. Self excitation in equity indices. [Thesis]. Queensland University of Technology; 2012. Available from: https://eprints.qut.edu.au/63629/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

University of New South Wales

24. Narula, Karan. Compressed estimation in coupled high-dimensional processes.

Degree: Mechanical & Manufacturing Engineering, 2019, University of New South Wales

URL: http://handle.unsw.edu.au/1959.4/63269 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:60059/SOURCE02?view=true

► The state estimation of high-dimensional problems is a topic of great interest in diverse research and application areas. In such problems, the conventional methods, although… (more)

▼ The state estimation of high-dimensional problems is a topic of great interest in diverse research and application areas. In such problems, the conventional methods, although highly capable and powerful, suffer from the high-computational requirement. Compressed Estimation approaches, such as the Generalised Compressed Kalman Filter (GCKF), are capable of reducing the computational cost and complexity of high-dimensional and high-frequency data assimilation problems; usually without sacrificing optimality. However, the application of a compressed estimation process is limited to a class of problems which inherently allow the estimation process to be divided, at certain intervals of times, into a set of lower-dimensional problems. This limitation prohibits applying the compressing techniques for estimating coupled high-dimensional processes.To this end, the concepts of subsystem switching and information exchange architectures have been derived and explored in this thesis, for allowing the compressed estimators to mimic optimal full Gaussian estimators in coupled processes. Furthermore, concepts such as Marginalised Likelihood and Perfect Global update have been derived to allow the application of compressed estimation in overlapping architecture with certain assumptions. The performances of these methods have been verified through its application in solving usual types of stochastic partial differential equations (SPDEs), where the compressed estimator is compared against the full Gaussian estimator. The proposed solution is general and can be adapted for non-linear estimation with the assumption of Gaussian Probability Density Function (PDF). The general framework is shown along with the example of replacing the Kalman Filter (KF) core with the better-suited point-based Gaussian filter core, such as Unscented Kalman Filter (UKF) or Cubature Kalman Filter (CuKF), for solving non-linear SPDEs. The compressed Gaussian filter is later applied to solve the usual estimation problems in the literature such as dual estimation and 2D Simultaneous Localization and Mapping (SLAM). In all these cases, substantial computational savings can be achieved when dealing with high-dimensional and high-frequency data assimilation.Following on from this research, the developed framework can be adapted and applied in a wide range of engineering and scientific fields. Advisors/Committee Members: Guivant, Jose, Mechanical & Manufacturing Engineering, Faculty of Engineering, UNSW.

Subjects/Keywords: Stochastic PDEs; Generalised compressed kalman filter; High-dimensional estimation; Estimation; Kalman filters; Probability density function; Filtering algorithms; Stochastic processes; Filtering theory; Nonlinear estimation

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APA (6^th Edition):

Narula, K. (2019). Compressed estimation in coupled high-dimensional processes. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/63269 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:60059/SOURCE02?view=true

Chicago Manual of Style (16^th Edition):

Narula, Karan. “Compressed estimation in coupled high-dimensional processes.” 2019. Doctoral Dissertation, University of New South Wales. Accessed March 04, 2021. http://handle.unsw.edu.au/1959.4/63269 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:60059/SOURCE02?view=true.

MLA Handbook (7^th Edition):

Narula, Karan. “Compressed estimation in coupled high-dimensional processes.” 2019. Web. 04 Mar 2021.

Vancouver:

Narula K. Compressed estimation in coupled high-dimensional processes. [Internet] [Doctoral dissertation]. University of New South Wales; 2019. [cited 2021 Mar 04]. Available from: http://handle.unsw.edu.au/1959.4/63269 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:60059/SOURCE02?view=true.

Council of Science Editors:

Narula K. Compressed estimation in coupled high-dimensional processes. [Doctoral Dissertation]. University of New South Wales; 2019. Available from: http://handle.unsw.edu.au/1959.4/63269 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:60059/SOURCE02?view=true

Texas A&M University

25. Lee, Deok-Jin. Nonlinear bayesian filtering with applications to estimation and navigation.

Degree: PhD, Aerospace Engineering, 2005, Texas A&M University

URL: http://hdl.handle.net/1969.1/2269

► In principle, general approaches to optimal nonlinear filtering can be described in a unified way from the recursive Bayesian approach. The central idea to this… (more)

▼ In principle, general approaches to optimal nonlinear filtering can be described in a unified way from the recursive Bayesian approach. The central idea to this recur- sive Bayesian estimation is to determine the probability density function of the state vector of the nonlinear systems conditioned on the available measurements. However, the optimal exact solution to this Bayesian filtering problem is intractable since it requires an infinite dimensional process. For practical nonlinear filtering applications approximate solutions are required. Recently efficient and accurate approximate non- linear filters as alternatives to the extended Kalman filter are proposed for recursive nonlinear estimation of the states and parameters of dynamical systems. First, as sampling-based nonlinear filters, the sigma point filters, the unscented Kalman fil- ter and the divided difference filter are investigated. Secondly, a direct numerical nonlinear filter is introduced where the state conditional probability density is calcu- lated by applying fast numerical solvers to the Fokker-Planck equation in continuous- discrete system models. As simulation-based nonlinear filters, a universally effective algorithm, called the sequential Monte Carlo filter, that recursively utilizes a set of weighted samples to approximate the distributions of the state variables or param- eters, is investigated for dealing with nonlinear and non-Gaussian systems. Recentparticle filtering algorithms, which are developed independently in various engineer- ing fields, are investigated in a unified way. Furthermore, a new type of particle filter is proposed by integrating the divided difference filter with a particle filtering framework, leading to the divided difference particle filter. Sub-optimality of the ap- proximate nonlinear filters due to unknown system uncertainties can be compensated by using an adaptive filtering method that estimates both the state and system error statistics. For accurate identification of the time-varying parameters of dynamic sys- tems, new adaptive nonlinear filters that integrate the presented nonlinear filtering algorithms with noise estimation algorithms are derived. For qualitative and quantitative performance analysis among the proposed non- linear filters, systematic methods for measuring the nonlinearities, biasness, and op- timality of the proposed nonlinear filters are introduced. The proposed nonlinear optimal and sub-optimal filtering algorithms with applications to spacecraft orbit es- timation and autonomous navigation are investigated. Simulation results indicate that the advantages of the proposed nonlinear filters make these attractive alterna- tives to the extended Kalman filter. Advisors/Committee Members: Alfriend, Kyle T. (advisor), Junkins, John L. (committee member), Parlos, Alexander (committee member), Vadali, Srinivas R. (committee member).

Subjects/Keywords: statistical nonlinear filtering; estimation and navigation; Bayesian filter

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

APA (6^th Edition):

Lee, D. (2005). Nonlinear bayesian filtering with applications to estimation and navigation. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/2269

Chicago Manual of Style (16^th Edition):

Lee, Deok-Jin. “Nonlinear bayesian filtering with applications to estimation and navigation.” 2005. Doctoral Dissertation, Texas A&M University. Accessed March 04, 2021. http://hdl.handle.net/1969.1/2269.

MLA Handbook (7^th Edition):

Lee, Deok-Jin. “Nonlinear bayesian filtering with applications to estimation and navigation.” 2005. Web. 04 Mar 2021.

Vancouver:

Lee D. Nonlinear bayesian filtering with applications to estimation and navigation. [Internet] [Doctoral dissertation]. Texas A&M University; 2005. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1969.1/2269.

Council of Science Editors:

Lee D. Nonlinear bayesian filtering with applications to estimation and navigation. [Doctoral Dissertation]. Texas A&M University; 2005. Available from: http://hdl.handle.net/1969.1/2269

Texas A&M University

26. Kumar, Mrinal. Design and Analysis of Stochastic Dynamical Systems with Fokker-Planck Equation.

Degree: PhD, Aerospace Engineering, 2011, Texas A&M University

URL: http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7500

► This dissertation addresses design and analysis aspects of stochastic dynamical systems using Fokker-Planck equation (FPE). A new numerical methodology based on the partition of unity… (more)

▼ This dissertation addresses design and analysis aspects of stochastic dynamical systems using Fokker-Planck equation (FPE). A new numerical methodology based on the partition of unity meshless paradigm is developed to tackle the greatest hurdle in successful numerical solution of FPE, namely the curse of dimensionality. A local variational form of the Fokker-Planck operator is developed with provision for h- and p- refinement. The resulting high dimensional weak form integrals are evaluated using quasi Monte-Carlo techniques. Spectral analysis of the discretized Fokker- Planck operator, followed by spurious mode rejection is employed to construct a new semi-analytical algorithm to obtain near real-time approximations of transient FPE response of high dimensional nonlinear dynamical systems in terms of a reduced subset of admissible modes. Numerical evidence is provided showing that the curse of dimensionality associated with FPE is broken by the proposed technique, while providing problem size reduction of several orders of magnitude. In addition, a simple modification of norm in the variational formulation is shown to improve quality of approximation significantly while keeping the problem size fixed. Norm modification is also employed as part of a recursive methodology for tracking the optimal finite domain to solve FPE numerically. The basic tools developed to solve FPE are applied to solving problems in nonlinear stochastic optimal control and nonlinear filtering. A policy iteration algorithm for stochastic dynamical systems is implemented in which successive approximations of a forced backward Kolmogorov equation (BKE) is shown to converge to the solution of the corresponding Hamilton Jacobi Bellman (HJB) equation. Several examples, including a four-state missile autopilot design for pitch control, are considered. Application of the FPE solver to nonlinear filtering is considered with special emphasis on situations involving long durations of propagation in between measurement updates, which is implemented as a weak form of the Bayes rule. A nonlinear filter is formulated that provides complete probabilistic state information conditioned on measurements. Examples with long propagation times are considered to demonstrate benefits of using the FPE based approach to filtering. Advisors/Committee Members: Chakravorty, Suman (advisor), Junkins, John L. (advisor), Vadali, Srinivas R. (committee member), Hyland, David (committee member), Bhattacharyya, Shankar P. (committee member).

Subjects/Keywords: Stochastic dynamical systems; Fokker-Planck equation; Meshless finite-element methods; Nonlinear filtering; Stochastic optimal control; Partition of unity finite-element method

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APA (6^th Edition):

Kumar, M. (2011). Design and Analysis of Stochastic Dynamical Systems with Fokker-Planck Equation. (Doctoral Dissertation). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7500

Chicago Manual of Style (16^th Edition):

Kumar, Mrinal. “Design and Analysis of Stochastic Dynamical Systems with Fokker-Planck Equation.” 2011. Doctoral Dissertation, Texas A&M University. Accessed March 04, 2021. http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7500.

MLA Handbook (7^th Edition):

Kumar, Mrinal. “Design and Analysis of Stochastic Dynamical Systems with Fokker-Planck Equation.” 2011. Web. 04 Mar 2021.

Vancouver:

Kumar M. Design and Analysis of Stochastic Dynamical Systems with Fokker-Planck Equation. [Internet] [Doctoral dissertation]. Texas A&M University; 2011. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7500.

Council of Science Editors:

Kumar M. Design and Analysis of Stochastic Dynamical Systems with Fokker-Planck Equation. [Doctoral Dissertation]. Texas A&M University; 2011. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7500

27. Bui, Van Bien. La stabilité du filtre non-linéaire en temps continu : The stability of non-linear filter in continuous time.

Degree: Docteur es, Mathématiques, 2016, Nice

URL: http://www.theses.fr/2016NICE4002

►

Le problème de filtrage consiste à estimer l'état d'un système dynamique, appelé signal qui est souvent un processus markovien, à partir d'observation bruitées des états… (more)

Subjects/Keywords: Filtrage non-linéaire; Stabilité du filtre optimal; Filtre robuste; Nonlinear filtering; Stability of the optimal filter; Robust filter

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

APA (6^th Edition):

Bui, V. B. (2016). La stabilité du filtre non-linéaire en temps continu : The stability of non-linear filter in continuous time. (Doctoral Dissertation). Nice. Retrieved from http://www.theses.fr/2016NICE4002

Chicago Manual of Style (16^th Edition):

Bui, Van Bien. “La stabilité du filtre non-linéaire en temps continu : The stability of non-linear filter in continuous time.” 2016. Doctoral Dissertation, Nice. Accessed March 04, 2021. http://www.theses.fr/2016NICE4002.

MLA Handbook (7^th Edition):

Bui, Van Bien. “La stabilité du filtre non-linéaire en temps continu : The stability of non-linear filter in continuous time.” 2016. Web. 04 Mar 2021.

Vancouver:

Bui VB. La stabilité du filtre non-linéaire en temps continu : The stability of non-linear filter in continuous time. [Internet] [Doctoral dissertation]. Nice; 2016. [cited 2021 Mar 04]. Available from: http://www.theses.fr/2016NICE4002.

Council of Science Editors:

Bui VB. La stabilité du filtre non-linéaire en temps continu : The stability of non-linear filter in continuous time. [Doctoral Dissertation]. Nice; 2016. Available from: http://www.theses.fr/2016NICE4002

Queensland University of Technology

28. Techakesari, Onvaree. Filter and control performance bounds in the presence of model uncertainties with aerospace applications.

Degree: 2013, Queensland University of Technology

URL: https://eprints.qut.edu.au/63956/

► This thesis establishes performance properties for approximate filters and controllers that are designed on the basis of approximate dynamic system representations. These performance properties provide… (more)

Subjects/Keywords: Approximating Filter; Nonlinear Filtering; Filter Stability; Model Approximation; Relative Entropy; Hybrid Filter; Control Stability; Air Traffic Separation Management; Practical Stability

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APA (6^th Edition):

Techakesari, O. (2013). Filter and control performance bounds in the presence of model uncertainties with aerospace applications. (Thesis). Queensland University of Technology. Retrieved from https://eprints.qut.edu.au/63956/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Techakesari, Onvaree. “Filter and control performance bounds in the presence of model uncertainties with aerospace applications.” 2013. Thesis, Queensland University of Technology. Accessed March 04, 2021. https://eprints.qut.edu.au/63956/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Techakesari, Onvaree. “Filter and control performance bounds in the presence of model uncertainties with aerospace applications.” 2013. Web. 04 Mar 2021.

Vancouver:

Techakesari O. Filter and control performance bounds in the presence of model uncertainties with aerospace applications. [Internet] [Thesis]. Queensland University of Technology; 2013. [cited 2021 Mar 04]. Available from: https://eprints.qut.edu.au/63956/.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Techakesari O. Filter and control performance bounds in the presence of model uncertainties with aerospace applications. [Thesis]. Queensland University of Technology; 2013. Available from: https://eprints.qut.edu.au/63956/

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Linköping University

29. Rosén, Jakob. A Framework for Nonlinear Filtering in MATLAB.

Degree: Electrical Engineering, 2005, Linköping University

URL: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-5190

► The object of this thesis is to provide a MATLAB framework for nonlinear filtering in general, and particle filtering in particular. This is done… (more)

Subjects/Keywords: Nonlinear Filtering; Particle Filters; EKF; MATLAB; Automatic control; Reglerteknik

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APA (6^th Edition):

Rosén, J. (2005). A Framework for Nonlinear Filtering in MATLAB. (Thesis). Linköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-5190

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Rosén, Jakob. “A Framework for Nonlinear Filtering in MATLAB.” 2005. Thesis, Linköping University. Accessed March 04, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-5190.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Rosén, Jakob. “A Framework for Nonlinear Filtering in MATLAB.” 2005. Web. 04 Mar 2021.

Vancouver:

Rosén J. A Framework for Nonlinear Filtering in MATLAB. [Internet] [Thesis]. Linköping University; 2005. [cited 2021 Mar 04]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-5190.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Rosén J. A Framework for Nonlinear Filtering in MATLAB. [Thesis]. Linköping University; 2005. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-5190

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

George Mason University

30. Ravichandran, Suraj. Comparison of Di erent Kalman Filters for Application to Mobile Robotics .

Degree: 2014, George Mason University

URL: http://hdl.handle.net/1920/8997

► The problem of state estimation of the mobile robot's trajectory being a nonlinear one, the intent of this thesis is to go beyond the realm… (more)

Subjects/Keywords: Kalman Filtering; Nonlinear Kalman Filters; Unscented Kalman Filters; mobile robotics; Iterated Extend Kalman Filter; Extended Kalman Filter

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

APA (6^th Edition):

Ravichandran, S. (2014). Comparison of Di erent Kalman Filters for Application to Mobile Robotics . (Thesis). George Mason University. Retrieved from http://hdl.handle.net/1920/8997

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^th Edition):

Ravichandran, Suraj. “Comparison of Di erent Kalman Filters for Application to Mobile Robotics .” 2014. Thesis, George Mason University. Accessed March 04, 2021. http://hdl.handle.net/1920/8997.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^th Edition):

Ravichandran, Suraj. “Comparison of Di erent Kalman Filters for Application to Mobile Robotics .” 2014. Web. 04 Mar 2021.

Vancouver:

Ravichandran S. Comparison of Di erent Kalman Filters for Application to Mobile Robotics . [Internet] [Thesis]. George Mason University; 2014. [cited 2021 Mar 04]. Available from: http://hdl.handle.net/1920/8997.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Ravichandran S. Comparison of Di erent Kalman Filters for Application to Mobile Robotics . [Thesis]. George Mason University; 2014. Available from: http://hdl.handle.net/1920/8997

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Open Access Theses and Dissertations