Least-Mean-Square Adaptive Filters

Least-Mean-Square Adaptive Filters

Author: Simon Haykin

Publisher: John Wiley & Sons

Published: 2003-09-08

Total Pages: 516

ISBN-13: 9780471215707

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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.


Adaptive Filtering

Adaptive Filtering

Author: Alexander D. Poularikas

Publisher: CRC Press

Published: 2017-12-19

Total Pages: 363

ISBN-13: 1482253364

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Adaptive filters are used in many diverse applications, appearing in everything from military instruments to cellphones and home appliances. Adaptive Filtering: Fundamentals of Least Mean Squares with MATLAB® covers the core concepts of this important field, focusing on a vital part of the statistical signal processing area—the least mean square (LMS) adaptive filter. This largely self-contained text: Discusses random variables, stochastic processes, vectors, matrices, determinants, discrete random signals, and probability distributions Explains how to find the eigenvalues and eigenvectors of a matrix and the properties of the error surfaces Explores the Wiener filter and its practical uses, details the steepest descent method, and develops the Newton’s algorithm Addresses the basics of the LMS adaptive filter algorithm, considers LMS adaptive filter variants, and provides numerous examples Delivers a concise introduction to MATLAB®, supplying problems, computer experiments, and more than 110 functions and script files Featuring robust appendices complete with mathematical tables and formulas, Adaptive Filtering: Fundamentals of Least Mean Squares with MATLAB® clearly describes the key principles of adaptive filtering and effectively demonstrates how to apply them to solve real-world problems.


Kernel Adaptive Filtering

Kernel Adaptive Filtering

Author: Weifeng Liu

Publisher: John Wiley & Sons

Published: 2011-09-20

Total Pages: 167

ISBN-13: 1118211219

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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.


Pipelined Adaptive Digital Filters

Pipelined Adaptive Digital Filters

Author: Naresh R. Shanbhag

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 194

ISBN-13: 1461526787

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Adaptive filtering is commonly used in many communication applications including speech and video predictive coding, mobile radio, ISDN subscriber loops, and multimedia systems. Existing adaptive filtering topologies are non-concurrent and cannot be pipelined. Pipelined Adaptive Digital Filters presents new pipelined topologies which are useful in reducing area and power and in increasing speed. If the adaptive filter portion of a system suffers from a power-speed-area bottleneck, a solution is provided. Pipelined Adaptive Digital Filters is required reading for all users of adaptive digital filtering algorithms. Algorithm, application and integrated circuit chip designers can learn how their algorithms can be tailored and implemented with lower area and power consumption and with higher speed. The relaxed look-ahead techniques are used to design families of new topologies for many adaptive filtering applications including least mean square and lattice adaptive filters, adaptive differential pulse code modulation coders, adaptive differential vector quantizers, adaptive decision feedback equalizers and adaptive Kalman filters. Those who use adaptive filtering in communications, signal and image processing algorithms can learn the basis of relaxed look-ahead pipelining and can use their own relaxations to design pipelined topologies suitable for their applications. Pipelined Adaptive Digital Filters is especially useful to designers of communications, speech, and video applications who deal with adaptive filtering, those involved with design of modems, wireless systems, subscriber loops, beam formers, and system identification applications. This book can also be used as a text for advanced courses on the topic.


Adaptive Processing

Adaptive Processing

Author: Odile Macchi

Publisher: Wiley

Published: 1995-05-09

Total Pages: 476

ISBN-13: 9780471934035

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Adaptive Processing The Least Mean Squares Approach with Applications in Transmission Odile Macchi Laboratoire des Signaux et Systèmes France Providing an in-depth study of adaptive systems used in digital signal processing, this book presents both theoretical concepts and applications. The author provides a rigorous investigation of LMS adaptive processing and exemplifies the concepts with channel data equalisation, echo cancellation and prediction for bit rate reduction. The text is divided into four key areas: Adaptive transversal filters, covering their transient aspects (speed of convergence) and their steady-state (fluctuations and misadjustment). Implementation aspects (binary word lengths and simplified sign algorithms). Tracking performance of adaptive filters in a time varying context. Adaptive recursive filters and their stability problems. This book presents a comprehensive mathematical treatment of adaptive processes based on realistic assumptions such as the finite memory of inputs. The author uses original research material organised in a unified framework. Particularly original are the chapters on sign algorithms, tracking performance and recursive filters in the presence of narrowband inputs. This comprehensive text will be of considerable interest to research students in digital communications and signal processing. In particular, this will be a valuable reference for professional practitioners working in the industrial R & D market.


Complex Valued Nonlinear Adaptive Filters

Complex Valued Nonlinear Adaptive Filters

Author: Danilo P. Mandic

Publisher: John Wiley & Sons

Published: 2009-04-20

Total Pages: 344

ISBN-13: 0470742631

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This book was written in response to the growing demand for a text that provides a unified treatment of linear and nonlinear complex valued adaptive filters, and methods for the processing of general complex signals (circular and noncircular). It brings together adaptive filtering algorithms for feedforward (transversal) and feedback architectures and the recent developments in the statistics of complex variable, under the powerful frameworks of CR (Wirtinger) calculus and augmented complex statistics. This offers a number of theoretical performance gains, which is illustrated on both stochastic gradient algorithms, such as the augmented complex least mean square (ACLMS), and those based on Kalman filters. This work is supported by a number of simulations using synthetic and real world data, including the noncircular and intermittent radar and wind signals.


Advances in Signal Processing and Intelligent Recognition Systems

Advances in Signal Processing and Intelligent Recognition Systems

Author: Sabu M. Thampi

Publisher: Springer Science & Business Media

Published: 2014-02-14

Total Pages: 607

ISBN-13: 3319049607

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This edited volume contains a selection of refereed and revised papers originally presented at the International Symposium on Signal Processing and Intelligent Recognition Systems (SIRS-2014), March 13-15, 2014, Trivandrum, India. The program committee received 134 submissions from 11 countries. Each paper was peer reviewed by at least three or more independent referees of the program committee and the 52 papers were finally selected. The papers offer stimulating insights into Pattern Recognition, Machine Learning and Knowledge-Based Systems; Signal and Speech Processing; Image and Video Processing; Mobile Computing and Applications and Computer Vision. The book is directed to the researchers and scientists engaged in various field of signal processing and related areas.


Adaptive Filtering Primer with MATLAB

Adaptive Filtering Primer with MATLAB

Author: Alexander D. Poularikas

Publisher: CRC Press

Published: 2017-12-19

Total Pages: 242

ISBN-13: 1351837834

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Because of the wide use of adaptive filtering in digital signal processing and, because most of the modern electronic devices include some type of an adaptive filter, a text that brings forth the fundamentals of this field was necessary. The material and the principles presented in this book are easily accessible to engineers, scientists, and students who would like to learn the fundamentals of this field and have a background at the bachelor level. Adaptive Filtering Primer with MATLAB® clearly explains the fundamentals of adaptive filtering supported by numerous examples and computer simulations. The authors introduce discrete-time signal processing, random variables and stochastic processes, the Wiener filter, properties of the error surface, the steepest descent method, and the least mean square (LMS) algorithm. They also supply many MATLAB® functions and m-files along with computer experiments to illustrate how to apply the concepts to real-world problems. The book includes problems along with hints, suggestions, and solutions for solving them. An appendix on matrix computations completes the self-contained coverage. With applications across a wide range of areas, including radar, communications, control, medical instrumentation, and seismology, Adaptive Filtering Primer with MATLAB® is an ideal companion for quick reference and a perfect, concise introduction to the field.


Adaptive Filters

Adaptive Filters

Author: Ali H. Sayed

Publisher: John Wiley & Sons

Published: 2011-10-11

Total Pages: 1295

ISBN-13: 1118210840

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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.


Adaptive Filters

Adaptive Filters

Author: Behrouz Farhang-Boroujeny

Publisher: John Wiley & Sons

Published: 2013-04-02

Total Pages: 800

ISBN-13: 111859133X

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This second edition of Adaptive Filters: Theory and Applications has been updated throughout to reflect the latest developments in this field; notably an increased coverage given to the practical applications of the theory to illustrate the much broader range of adaptive filters applications developed in recent years. The book offers an easy to understand approach to the theory and application of adaptive filters by clearly illustrating how the theory explained in the early chapters of the book is modified for the various applications discussed in detail in later chapters. This integrated approach makes the book a valuable resource for graduate students; and the inclusion of more advanced applications including antenna arrays and wireless communications makes it a suitable technical reference for engineers, practitioners and researchers. Key features: • Offers a thorough treatment of the theory of adaptive signal processing; incorporating new material on transform domain, frequency domain, subband adaptive filters, acoustic echo cancellation and active noise control. • Provides an in-depth study of applications which now includes extensive coverage of OFDM, MIMO and smart antennas. • Contains exercises and computer simulation problems at the end of each chapter. • Includes a new companion website hosting MATLAB® simulation programs which complement the theoretical analyses, enabling the reader to gain an in-depth understanding of the behaviours and properties of the various adaptive algorithms.