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Author : Colin F. N. Cowan
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (592 download)
Download or read book Nonlinear and Non-Gaussian Signal Processing written by Colin F. N. Cowan and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Colin F. N. Cowan
Publisher :
ISBN 13 :
Total Pages : 63 pages
Book Rating : 4.:/5 (437 download)
Download or read book Special Section on Nonlinear and Non-Gaussian Signal Processing written by Colin F. N. Cowan and published by . This book was released on 2004 with total page 63 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Gonzalo R. Arce
Publisher : John Wiley & Sons
ISBN 13 : 0471691844
Total Pages : 483 pages
Book Rating : 4.4/5 (716 download)
Download or read book Nonlinear Signal Processing written by Gonzalo R. Arce and published by John Wiley & Sons. This book was released on 2005-01-03 with total page 483 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear Signal Processing: A Statistical Approach focuses on unifying the study of a broad and important class of nonlinear signal processing algorithms which emerge from statistical estimation principles, and where the underlying signals are non-Gaussian, rather than Gaussian, processes. Notably, by concentrating on just two non-Gaussian models, a large set of tools is developed that encompass a large portion of the nonlinear signal processing tools proposed in the literature over the past several decades. Key features include: * Numerous problems at the end of each chapter to aid development and understanding * Examples and case studies provided throughout the book in a wide range of applications bring the text to life and place the theory into context * A set of 60+ MATLAB software m-files allowing the reader to quickly design and apply any of the nonlinear signal processing algorithms described in the book to an application of interest is available on the accompanying FTP site.
Author : Edward J. Wegman
Publisher : Springer Science & Business Media
ISBN 13 : 1461388597
Total Pages : 246 pages
Book Rating : 4.4/5 (613 download)
Download or read book Topics in Non-Gaussian Signal Processing written by Edward J. Wegman and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Non-Gaussian Signal Processing is a child of a technological push. It is evident that we are moving from an era of simple signal processing with relatively primitive electronic cir cuits to one in which digital processing systems, in a combined hardware-software configura. tion, are quite capable of implementing advanced mathematical and statistical procedures. Moreover, as these processing techniques become more sophisticated and powerful, the sharper resolution of the resulting system brings into question the classic distributional assumptions of Gaussianity for both noise and signal processes. This in turn opens the door to a fundamental reexamination of structure and inference methods for non-Gaussian sto chastic processes together with the application of such processes as models in the context of filtering, estimation, detection and signal extraction. Based on the premise that such a fun damental reexamination was timely, in 1981 the Office of Naval Research initiated a research effort in Non-Gaussian Signal Processing under the Selected Research Opportunities Program.
Author : W. J. Fitzgerald
Publisher : Cambridge University Press
ISBN 13 : 9780521800440
Total Pages : 510 pages
Book Rating : 4.8/5 (4 download)
Download or read book Nonlinear and Nonstationary Signal Processing written by W. J. Fitzgerald and published by Cambridge University Press. This book was released on 2000 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: Signal processing, nonlinear data analysis, nonlinear time series, nonstationary processes.
Author : Kenneth E. Barner
Publisher : CRC Press
ISBN 13 : 0203010418
Total Pages : 560 pages
Book Rating : 4.2/5 (3 download)
Download or read book Nonlinear Signal and Image Processing written by Kenneth E. Barner and published by CRC Press. This book was released on 2003-11-24 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear signal and image processing methods are fast emerging as an alternative to established linear methods for meeting the challenges of increasingly sophisticated applications. Advances in computing performance and nonlinear theory are making nonlinear techniques not only viable, but practical. This book details recent advances in nonl
Author : Ronald R. Mohler
Publisher : Springer
ISBN 13 : 9783662211069
Total Pages : 150 pages
Book Rating : 4.2/5 (11 download)
Download or read book Nonlinear Time Series and Signal Processing written by Ronald R. Mohler and published by Springer. This book was released on 2014-03-12 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph provides a sample of relevant new results on dynamical nonlinear statistical modeling and estimation which forms a basis for more effective signal processing, decision and control. While the research literature is rich in linear Gaussian methodologies, new contributions to the most relevant area of nonlinear and non-Gaussian processes have been scarce. Among the significant areas of application for which such methodologies are needed are: economics, biology, immunology, underwater acoustics, electric power generation, chemical process control, and variable structure systems in general. The latter include adaptive, intelligent, and decomposing mathematical structures or processes. The volume includes ten research papers on theory, computational methods, and applications. Topics include filtering with application to inertial navigation, structural-change detection, bilinear time-series models, bispectral estimation, threshold models, catastrophic models and a generalized eigenstructure method.
Author : Kumar Pakki Bharani Chandra
Publisher : Springer
ISBN 13 : 3030017974
Total Pages : 184 pages
Book Rating : 4.0/5 (3 download)
Download or read book Nonlinear Filtering written by Kumar Pakki Bharani Chandra and published by Springer. This book was released on 2018-11-20 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives readers in-depth know-how on methods of state estimation for nonlinear control systems. It starts with an introduction to dynamic control systems and system states and a brief description of the Kalman filter. In the following chapters, various state estimation techniques for nonlinear systems are discussed, including the extended, unscented and cubature Kalman filters. The cubature Kalman filter and its variants are introduced in particular detail because of their efficiency and their ability to deal with systems with Gaussian and/or non-Gaussian noise. The book also discusses information-filter and square-root-filtering algorithms, useful for state estimation in some real-time control system design problems. A number of case studies are included in the book to illustrate the application of various nonlinear filtering algorithms. Nonlinear Filtering is written for academic and industrial researchers, engineers and research students who are interested in nonlinear control systems analysis and design. The chief features of the book include: dedicated coverage of recently developed nonlinear, Jacobian-free, filtering algorithms; examples illustrating the use of nonlinear filtering algorithms in real-world applications; detailed derivation and complete algorithms for nonlinear filtering methods, which help readers to a fundamental understanding and easier coding of those algorithms; and MATLAB® codes associated with case-study applications, which can be downloaded from the Springer Extra Materials website.
Author : Ioannis Pitas
Publisher : Springer Science & Business Media
ISBN 13 : 1475760175
Total Pages : 402 pages
Book Rating : 4.4/5 (757 download)
Download or read book Nonlinear Digital Filters written by Ioannis Pitas and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: The function of a filter is to transform a signal into another one more suit able for a given purpose. As such, filters find applications in telecommunica tions, radar, sonar, remote sensing, geophysical signal processing, image pro cessing, and computer vision. Numerous authors have considered deterministic and statistical approaches for the study of passive, active, digital, multidimen sional, and adaptive filters. Most of the filters considered were linear although the theory of nonlinear filters is developing rapidly, as it is evident by the numerous research papers and a few specialized monographs now available. Our research interests in this area created opportunity for cooperation and co authored publications during the past few years in many nonlinear filter families described in this book. As a result of this cooperation and a visit from John Pitas on a research leave at the University of Toronto in September 1988, the idea for this book was first conceived. The difficulty in writing such a mono graph was that the area seemed fragmented and no general theory was available to encompass the many different kinds of filters presented in the literature. However, the similarities of some families of nonlinear filters and the need for such a monograph providing a broad overview of the whole area made the pro ject worthwhile. The result is the book now in your hands, typeset at the Department of Electrical Engineering of the University of Toronto during the summer of 1989.
Author : Peyman Setoodeh
Publisher : John Wiley & Sons
ISBN 13 : 1119078156
Total Pages : 308 pages
Book Rating : 4.1/5 (19 download)
Download or read book Nonlinear Filters written by Peyman Setoodeh and published by John Wiley & Sons. This book was released on 2022-03-04 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: NONLINEAR FILTERS Discover the utility of using deep learning and (deep) reinforcement learning in deriving filtering algorithms with this insightful and powerful new resource Nonlinear Filters: Theory and Applications delivers an insightful view on state and parameter estimation by merging ideas from control theory, statistical signal processing, and machine learning. Taking an algorithmic approach, the book covers both classic and machine learning-based filtering algorithms. Readers of Nonlinear Filters will greatly benefit from the wide spectrum of presented topics including stability, robustness, computability, and algorithmic sufficiency. Readers will also enjoy: Organization that allows the book to act as a stand-alone, self-contained reference A thorough exploration of the notion of observability, nonlinear observers, and the theory of optimal nonlinear filtering that bridges the gap between different science and engineering disciplines A profound account of Bayesian filters including Kalman filter and its variants as well as particle filter A rigorous derivation of the smooth variable structure filter as a predictor-corrector estimator formulated based on a stability theorem, used to confine the estimated states within a neighborhood of their true values A concise tutorial on deep learning and reinforcement learning A detailed presentation of the expectation maximization algorithm and its machine learning-based variants, used for joint state and parameter estimation Guidelines for constructing nonparametric Bayesian models from parametric ones Perfect for researchers, professors, and graduate students in engineering, computer science, applied mathematics, and artificial intelligence, Nonlinear Filters: Theory and Applications will also earn a place in the libraries of those studying or practicing in fields involving pandemic diseases, cybersecurity, information fusion, augmented reality, autonomous driving, urban traffic network, navigation and tracking, robotics, power systems, hybrid technologies, and finance.
Author : Gordon Morison
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (141 download)
Download or read book Nonlinear Non-Gaussian Algorithms for Signal and Image Processing written by Gordon Morison and published by . This book was released on 2007 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jaakko Astola
Publisher : CRC Press
ISBN 13 : 100014111X
Total Pages : 292 pages
Book Rating : 4.0/5 (1 download)
Download or read book Fundamentals of Nonlinear Digital Filtering written by Jaakko Astola and published by CRC Press. This book was released on 2020-09-10 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundamentals of Nonlinear Digital Filtering is the first book of its kind, presenting and evaluating current methods and applications in nonlinear digital filtering. Written for professors, researchers, and application engineers, as well as for serious students of signal processing, this is the only book available that functions as both a reference handbook and a textbook. Solid introductory material, balanced coverage of theoretical and practical aspects, and dozens of examples provide you with a self-contained, comprehensive information source on nonlinear filtering and its applications.
Author : Huber, Marco
Publisher : KIT Scientific Publishing
ISBN 13 : 3731503387
Total Pages : 302 pages
Book Rating : 4.7/5 (315 download)
Download or read book Nonlinear Gaussian Filtering : Theory, Algorithms, and Applications written by Huber, Marco and published by KIT Scientific Publishing. This book was released on 2015-03-11 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: By restricting to Gaussian distributions, the optimal Bayesian filtering problem can be transformed into an algebraically simple form, which allows for computationally efficient algorithms. Three problem settings are discussed in this thesis: (1) filtering with Gaussians only, (2) Gaussian mixture filtering for strong nonlinearities, (3) Gaussian process filtering for purely data-driven scenarios. For each setting, efficient algorithms are derived and applied to real-world problems.
Author : Marcelo G.
Publisher : Springer Nature
ISBN 13 : 3031025350
Total Pages : 87 pages
Book Rating : 4.0/5 (31 download)
Download or read book Sequential Monte Carlo Methods for Nonlinear Discrete-Time Filtering written by Marcelo G. and published by Springer Nature. This book was released on 2022-06-01 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt: In these notes, we introduce particle filtering as a recursive importance sampling method that approximates the minimum-mean-square-error (MMSE) estimate of a sequence of hidden state vectors in scenarios where the joint probability distribution of the states and the observations is non-Gaussian and, therefore, closed-form analytical expressions for the MMSE estimate are generally unavailable. We begin the notes with a review of Bayesian approaches to static (i.e., time-invariant) parameter estimation. In the sequel, we describe the solution to the problem of sequential state estimation in linear, Gaussian dynamic models, which corresponds to the well-known Kalman (or Kalman-Bucy) filter. Finally, we move to the general nonlinear, non-Gaussian stochastic filtering problem and present particle filtering as a sequential Monte Carlo approach to solve that problem in a statistically optimal way. We review several techniques to improve the performance of particle filters, including importance function optimization, particle resampling, Markov Chain Monte Carlo move steps, auxiliary particle filtering, and regularized particle filtering. We also discuss Rao-Blackwellized particle filtering as a technique that is particularly well-suited for many relevant applications such as fault detection and inertial navigation. Finally, we conclude the notes with a discussion on the emerging topic of distributed particle filtering using multiple processors located at remote nodes in a sensor network. Throughout the notes, we often assume a more general framework than in most introductory textbooks by allowing either the observation model or the hidden state dynamic model to include unknown parameters. In a fully Bayesian fashion, we treat those unknown parameters also as random variables. Using suitable dynamic conjugate priors, that approach can be applied then to perform joint state and parameter estimation. Table of Contents: Introduction / Bayesian Estimation of Static Vectors / The Stochastic Filtering Problem / Sequential Monte Carlo Methods / Sampling/Importance Resampling (SIR) Filter / Importance Function Selection / Markov Chain Monte Carlo Move Step / Rao-Blackwellized Particle Filters / Auxiliary Particle Filter / Regularized Particle Filters / Cooperative Filtering with Multiple Observers / Application Examples / Summary
Author : Albert H. Nuttall
Publisher :
ISBN 13 :
Total Pages : 76 pages
Book Rating : 4.:/5 (326 download)
Download or read book Spectra and Covariances for "classical" Nonlinear Signal Processing Problems Involving Class A Non-Gaussian Noise written by Albert H. Nuttall and published by . This book was released on 1991 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Chunjian Li
Publisher :
ISBN 13 : 9788790834906
Total Pages : pages
Book Rating : 4.8/5 (349 download)
Download or read book Non-Gaussian, Non-stationary, and Nonlinear Signal Processing Methods written by Chunjian Li and published by . This book was released on 2006 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Haiquan Zhao
Publisher : Springer Nature
ISBN 13 : 3031208188
Total Pages : 271 pages
Book Rating : 4.0/5 (312 download)
Download or read book Efficient Nonlinear Adaptive Filters written by Haiquan Zhao and published by Springer Nature. This book was released on 2023-02-10 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the design, analysis, and application of nonlinear adaptive filters with the goal of improving efficient performance (ie the convergence speed, steady-state error, and computational complexity). The authors present a nonlinear adaptive filter, which is an important part of nonlinear system and digital signal processing and can be applied to diverse fields such as communications, control power system, radar sonar, etc. The authors also present an efficient nonlinear filter model and robust adaptive filtering algorithm based on the local cost function of optimal criterion to overcome non-Gaussian noise interference. The authors show how these achievements provide new theories and methods for robust adaptive filtering of nonlinear and non-Gaussian systems. The book is written for the scientist and engineer who are not necessarily an expert in the specific nonlinear filtering field but who want to learn about the current research and application. The book is also written to accompany a graduate/PhD course in the area of nonlinear system and adaptive signal processing.
