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Book Partial Update Least Square Adaptive Filtering

Download or read book Partial Update Least Square Adaptive Filtering written by Bei Xie and published by Springer Nature. This book was released on 2022-05-31 with total page 105 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive filters play an important role in the fields related to digital signal processing and communication, such as system identification, noise cancellation, channel equalization, and beamforming. In practical applications, the computational complexity of an adaptive filter is an important consideration. The Least Mean Square (LMS) algorithm is widely used because of its low computational complexity ($O(N)$) and simplicity in implementation. The least squares algorithms, such as Recursive Least Squares (RLS), Conjugate Gradient (CG), and Euclidean Direction Search (EDS), can converge faster and have lower steady-state mean square error (MSE) than LMS. However, their high computational complexity ($O(N^2)$) makes them unsuitable for many real-time applications. A well-known approach to controlling computational complexity is applying partial update (PU) method to adaptive filters. A partial update method can reduce the adaptive algorithm complexity by updating part of the weight vector instead of the entire vector or by updating part of the time. In the literature, there are only a few analyses of these partial update adaptive filter algorithms. Most analyses are based on partial update LMS and its variants. Only a few papers have addressed partial update RLS and Affine Projection (AP). Therefore, analyses for PU least-squares adaptive filter algorithms are necessary and meaningful. This monograph mostly focuses on the analyses of the partial update least-squares adaptive filter algorithms. Basic partial update methods are applied to adaptive filter algorithms including Least Squares CMA (LSCMA), EDS, and CG. The PU methods are also applied to CMA1-2 and NCMA to compare with the performance of the LSCMA. Mathematical derivation and performance analysis are provided including convergence condition, steady-state mean and mean-square performance for a time-invariant system. The steady-state mean and mean-square performance are also presented for a time-varying system. Computational complexity is calculated for each adaptive filter algorithm. Numerical examples are shown to compare the computational complexity of the PU adaptive filters with the full-update filters. Computer simulation examples, including system identification and channel equalization, are used to demonstrate the mathematical analysis and show the performance of PU adaptive filter algorithms. They also show the convergence performance of PU adaptive filters. The performance is compared between the original adaptive filter algorithms and different partial-update methods. The performance is also compared among similar PU least-squares adaptive filter algorithms, such as PU RLS, PU CG, and PU EDS. In addition to the generic applications of system identification and channel equalization, two special applications of using partial update adaptive filters are also presented. One application uses PU adaptive filters to detect Global System for Mobile Communication (GSM) signals in a local GSM system using the Open Base Transceiver Station (OpenBTS) and Asterisk Private Branch Exchange (PBX). The other application uses PU adaptive filters to do image compression in a system combining hyperspectral image compression and classification.

Book Adaptive Filtering

    Book Details:
  • Author : Paulo Sergio Ramirez Diniz
  • Publisher : Springer Science & Business Media
  • Release : 2002
  • ISBN : 9781402071256
  • Pages : 594 pages

Download or read book Adaptive Filtering written by Paulo Sergio Ramirez Diniz and published by Springer Science & Business Media. This book was released on 2002 with total page 594 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive Filtering: Algorithms and Practical Implementation, Second Edition, presents a concise overview of adaptive filtering, covering as many algorithms as possible in a unified form that avoids repetition and simplifies notation. It is suitable as a textbook for senior undergraduate or first-year graduate courses in adaptive signal processing and adaptive filters. The philosophy of the presentation is to expose the material with a solid theoretical foundation, to concentrate on algorithms that really work in a finite-precision implementation, and to provide easy access to working algorithms. Hence, practicing engineers and scientists will also find the book to be an excellent reference. This second edition contains a substantial amount of new material: -Two new chapters on nonlinear and subband adaptive filtering; -Linearly constrained Weiner filters and LMS algorithms; -LMS algorithm behavior in fast adaptation; -Affine projection algorithms; -Derivation smoothing; -MATLAB codes for algorithms. An instructor's manual, a set of master transparencies, and the MATLAB codes for all of the algorithms described in the text are also available. Useful to both professional researchers and students, the text includes 185 problems; over 38 examples, and over 130 illustrations. It is of primary interest to those working in signal processing, communications, and circuits and systems. It will also be of interest to those working in power systems, networks, learning systems, and intelligent systems.

Book Least Mean Square Adaptive Filters

Download or read book Least Mean Square Adaptive Filters written by Simon Haykin and published by Wiley-Interscience. This book was released on 2003-09-08 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: Table of contents

Book A Rapid Introduction to Adaptive Filtering

Download or read book A Rapid Introduction to Adaptive Filtering written by Leonardo Rey Vega and published by Springer Science & Business Media. This book was released on 2012-08-07 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, the authors provide insights into the basics of adaptive filtering, which are particularly useful for students taking their first steps into this field. They start by studying the problem of minimum mean-square-error filtering, i.e., Wiener filtering. Then, they analyze iterative methods for solving the optimization problem, e.g., the Method of Steepest Descent. By proposing stochastic approximations, several basic adaptive algorithms are derived, including Least Mean Squares (LMS), Normalized Least Mean Squares (NLMS) and Sign-error algorithms. The authors provide a general framework to study the stability and steady-state performance of these algorithms. The affine Projection Algorithm (APA) which provides faster convergence at the expense of computational complexity (although fast implementations can be used) is also presented. In addition, the Least Squares (LS) method and its recursive version (RLS), including fast implementations are discussed. The book closes with the discussion of several topics of interest in the adaptive filtering field.

Book Adaptive Filter Theory

Download or read book Adaptive Filter Theory written by Simon S. Haykin and published by . This book was released on 2002 with total page 944 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive Filter Theory, 4e, is ideal for courses in Adaptive Filters. Haykin examines both the mathematical theory behind various linear adaptive filters and the elements of supervised multilayer perceptrons. In its fourth edition, this highly successful book has been updated and refined to stay current with the field and develop concepts in as unified and accessible a manner as possible.

Book Adaptive Filtering

Download or read book Adaptive Filtering written by Paulo S.R. Diniz and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 582 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive Filtering: Algorithms and Practical Implementation, Second Edition, presents a concise overview of adaptive filtering, covering as many algorithms as possible in a unified form that avoids repetition and simplifies notation. It is suitable as a textbook for senior undergraduate or first-year graduate courses in adaptive signal processing and adaptive filters. The philosophy of the presentation is to expose the material with a solid theoretical foundation, to concentrate on algorithms that really work in a finite-precision implementation, and to provide easy access to working algorithms. Hence, practicing engineers and scientists will also find the book to be an excellent reference. This second edition contains a substantial amount of new material: -Two new chapters on nonlinear and subband adaptive filtering; -Linearly constrained Weiner filters and LMS algorithms; -LMS algorithm behavior in fast adaptation; -Affine projection algorithms; -Derivation smoothing; -MATLAB codes for algorithms.

Book Introduction to Adaptive Filters

Download or read book Introduction to Adaptive Filters written by Simon S. Haykin and published by . This book was released on 1984 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Partial Update Adaptive Signal Processing

Download or read book Partial Update Adaptive Signal Processing written by Kutluyil Doğançay and published by Academic Press. This book was released on 2008-09-17 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: Partial-update adaptive signal processing algorithms not only permit significant complexity reduction in adaptive filter implementations, but can also improve adaptive filter performance in telecommunications applications. This book gives state-of-the-art methods for the design and development of partial-update adaptive signal processing algorithms for use in systems development.Partial-Update Adaptive Signal Processing provides a comprehensive coverage of key partial updating schemes, giving detailed information on the theory and applications of acoustic and network echo cancellation, channel equalization and multiuser detection. It also examines convergence and stability issues for partial update algorithms, providing detailed complexity analysis and a unifying treatment of partial-update techniques.Features:• Advanced analysis and design tools• Application examples illustrating the use of partial-update adaptive signal processing• MATLAB codes for developed algorithms This unique reference will be of interest to signal processing and communications engineers, researchers, R&D engineers and graduate students."This is a very systematic and methodical treatment of an adaptive signal processing topic, of particular significance in power limited applications such as in wireless communication systems and smart ad hoc sensor networks. I am very happy to have this book on my shelf, not to gather dust, but to be consulted and used in my own research and teaching activities" – Professor A. G. Constantinides, Imperial College, LondonAbout the author:Kutluyil Dogançay is an associate professor of Electrical Engineering at the University of South Australia. His research interests span statistical and adaptive signal processing and he serves as a consultant to defence and private industry. He was the Signal Processing and Communications Program Chair of IDC Conference 2007, and is currently chair of the IEEE South Australia Communications and Signal Processing Chapter. - Advanced analysis and design tools - Algorithm summaries in tabular format - Case studies illustrate the application of partial update adaptive signal processing

Book Least Mean Square Adaptive Filters

Download or read book Least Mean Square Adaptive Filters written by Simon Haykin and published by John Wiley & Sons. This book was released on 2003-09-08 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: Edited by the original inventor of the technology. Includes contributions by the foremost experts in the field. The only book to cover these topics together.

Book Kernel Adaptive Filtering

Download or read book Kernel Adaptive Filtering written by Weifeng Liu and published by John Wiley & Sons. This book was released on 2011-09-20 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: Online learning from a signal processing perspective There is increased interest in kernel learning algorithms in neural networks and a growing need for nonlinear adaptive algorithms in advanced signal processing, communications, and controls. Kernel Adaptive Filtering is the first book to present a comprehensive, unifying introduction to online learning algorithms in reproducing kernel Hilbert spaces. Based on research being conducted in the Computational Neuro-Engineering Laboratory at the University of Florida and in the Cognitive Systems Laboratory at McMaster University, Ontario, Canada, this unique resource elevates the adaptive filtering theory to a new level, presenting a new design methodology of nonlinear adaptive filters. Covers the kernel least mean squares algorithm, kernel affine projection algorithms, the kernel recursive least squares algorithm, the theory of Gaussian process regression, and the extended kernel recursive least squares algorithm Presents a powerful model-selection method called maximum marginal likelihood Addresses the principal bottleneck of kernel adaptive filters—their growing structure Features twelve computer-oriented experiments to reinforce the concepts, with MATLAB codes downloadable from the authors' Web site Concludes each chapter with a summary of the state of the art and potential future directions for original research Kernel Adaptive Filtering is ideal for engineers, computer scientists, and graduate students interested in nonlinear adaptive systems for online applications (applications where the data stream arrives one sample at a time and incremental optimal solutions are desirable). It is also a useful guide for those who look for nonlinear adaptive filtering methodologies to solve practical problems.

Book Adaptive Filtering

Download or read book Adaptive Filtering written by Paulo S. R. Diniz and published by Springer Nature. This book was released on 2019-11-28 with total page 495 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the fifth edition of this textbook, author Paulo S.R. Diniz presents updated text on the basic concepts of adaptive signal processing and adaptive filtering. He first introduces the main classes of adaptive filtering algorithms in a unified framework, using clear notations that facilitate actual implementation. Algorithms are described in tables, which are detailed enough to allow the reader to verify the covered concepts. Examples address up-to-date problems drawn from actual applications. Several chapters are expanded and a new chapter ‘Kalman Filtering’ is included. The book provides a concise background on adaptive filtering, including the family of LMS, affine projection, RLS, set-membership algorithms and Kalman filters, as well as nonlinear, sub-band, blind, IIR adaptive filtering, and more. Problems are included at the end of chapters. A MATLAB package is provided so the reader can solve new problems and test algorithms. The book also offers easy access to working algorithms for practicing engineers.

Book Artificial Intelligence and Computational Intelligence

Download or read book Artificial Intelligence and Computational Intelligence written by Hepu Deng and published by Springer. This book was released on 2011-09-25 with total page 717 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three-volume proceedings contains revised selected papers from the Second International Conference on Artificial Intelligence and Computational Intelligence, AICI 2011, held in Taiyuan, China, in September 2011. The total of 265 high-quality papers presented were carefully reviewed and selected from 1073 submissions. The topics of Part I covered are: applications of artificial intelligence; applications of computational intelligence; automated problem solving; biomedical inforamtics and computation; brain models/cognitive science; data mining and knowledge discovering; distributed AI and agents; evolutionary programming; expert and decision support systems; fuzzy computation; fuzzy logic and soft computing; and genetic algorithms.

Book Adaptive Filters

    Book Details:
  • Author : Ali H. Sayed
  • Publisher : John Wiley & Sons
  • Release : 2011-10-11
  • ISBN : 1118210840
  • Pages : 1295 pages

Download or read book Adaptive Filters written by Ali H. Sayed and published by John Wiley & Sons. This book was released on 2011-10-11 with total page 1295 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive filtering is a topic of immense practical and theoretical value, having applications in areas ranging from digital and wireless communications to biomedical systems. This book enables readers to gain a gradual and solid introduction to the subject, its applications to a variety of topical problems, existing limitations, and extensions of current theories. The book consists of eleven parts?each part containing a series of focused lectures and ending with bibliographic comments, problems, and computer projects with MATLAB solutions.

Book Topics in Acoustic Echo and Noise Control

Download or read book Topics in Acoustic Echo and Noise Control written by Eberhard Hänsler and published by Springer Science & Business Media. This book was released on 2006-08-26 with total page 648 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book treats important topics in "Acoustic Echo and Noise Control" and reports the latest developments. Methods for enhancing the quality of transmitted speech signals are gaining growing attention in universities and in industrial development laboratories. This book, written by an international team of highly qualified experts, concentrates on the modern and advanced methods.

Book Low complexity Adaptive Filtering Algorithms Based on the Minimum L  infinity  norm Method

Download or read book Low complexity Adaptive Filtering Algorithms Based on the Minimum L infinity norm Method written by Abhishek Tandon and published by . This book was released on 2004 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The complexity of an adaptive filtering algorithm is proportional to the tap length of the filter and hence, may become computationally prohibitive for applications requiring a long filter tap. In this thesis, we provide a framework for developing low-complexity adaptive filter algorithms by utilizing the concept of partial-updating along with the technique of finding the gradient vector in the hyperplane based on the L ∞ -norm criterion. The resulting algorithm should have low-complexity not only because of the updating of only a subset of the filter coefficients at each time step, but also from the fact that updating a filter coefficient using the algorithm based on L ∞ -norm requires less number of operations compared to the L 2 -norm algorithm. Two specific coefficient selection techniques, namely the sequential and M -Max coefficient selection techniques, are considered in this thesis. Statistical analyses of these two algorithms are carried out to derive the evolution equations for the mean and mean-square of the filter coefficient misalignment as well as to obtain stability bounds on the step-size of the two algorithms. Further, these analyses are used to show that the algorithm employing the M -Max coefficient selection technique can achieve a convergence rate that is closest to the full update algorithm. As a consequence, even though there are various ways of selecting a subset of the filter coefficients, the study of the other techniques becomes redundant. Simulations are carried out to validate the results obtained from the statistical analyses of the algorithms. The concept of developing algorithms based on the partial-updating and L ∞ -norm is extended to proportionate adaptive filtering. Finally, the performance of the proposed adaptive filtering algorithms as well as that of the existing ones is studied in echo cancellation.

Book Adaptive Filtering

    Book Details:
  • Author : Wenping Cao
  • Publisher : BoD – Books on Demand
  • Release : 2021-10-20
  • ISBN : 1839623772
  • Pages : 154 pages

Download or read book Adaptive Filtering written by Wenping Cao and published by BoD – Books on Demand. This book was released on 2021-10-20 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: Active filters are key technologies in applications such as telecommunications, advanced control, smart grids, and green transport. This book provides an update of the latest technological progress in signal processing and adaptive filters, with a focus on Kalman filters and applications. It illustrates fundamentals and guides filter design for specific applications, primarily for graduate students, academics, and industrial engineers who are interested in the theoretical, experimental, and design aspects of active filter technologies.

Book Fundamentals of Adaptive Filtering

Download or read book Fundamentals of Adaptive Filtering written by Ali H. Sayed and published by John Wiley & Sons. This book was released on 2003-06-13 with total page 1172 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is based on a graduate level course offered by the author at UCLA and has been classed tested there and at other universities over a number of years. This will be the most comprehensive book on the market today providing instructors a wide choice in designing their courses. * Offers computer problems to illustrate real life applications for students and professionals alike * An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.