Adaptive Filter Theory
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.
Adaptive Filters
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,...
Adaptive Signal Processing
A treatment of adaptive signal processing featuring frequent use of examples.
Adaptive Filtering Primer with MATLAB
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®...
Adaptive Signal Processing: Next Generation Solutions
This book presents the latest research results in adaptive signal processing with an emphasis on important applications and theoretical advancements. Each chapter is self-contained, comprehensive in its coverage, and written by a leader in his or her field of specialty. A uniform style is maintained throughout the book and each chapter concludes with problems for readers to reinforce their understanding of the material presented. The book can be used as a reliable reference for researchers...
Kernel Adaptive Filtering: A Comprehensive Introduction
Reproducing kernel Hilbert spaces is a topic of great current interest for applications in signal processing, communications, and controls The first book to explain real-time learning algorithms in reproducing kernel Hilbert spaces, On-Line Kernel Learning includes simulations that illustrate the ideas discussed and demonstrate their applicability as well as MATLAB codes for simulations. This book is ideal for professionals and graduate students interested in nonlinear adaptive systems for...
Linear Estimation
This original work offers the most comprehensive and up-to-date treatment of the important subject of optimal linear estimation, which is encountered in many areas of engineering such as communications, control, and signal processing, and also several other fields, e.g., econometrics and statistics. The book not only highlights the most significant contributions to this field during the 20th century, including the works of Weiner and Kalman, but it does so in an original and novel manner...
Fundamentals of Adaptive Filtering
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...
Statistical and Adaptive Signal Processing: Spectral Estimation, Signal Modeling
This book is intended for graduate students at the first year or advanced graduate level in the areas of statistical and adaptive signal processing, as well as practicing engineers. The goal of this book is to provide a unified, complete, and practical treatment of spectral estimation, signal modeling, adaptive filtering, and array processing.
The text is written in an intuitive manner and includes many illustrative examples. In addition a sufficient number of computer based experiments are...
Active Noise Control Systems : Algorithms and DSP Implementations
Active noise control (ANC) is rapidly becoming the most effective way to reduce noises that can otherwise be very difficult and expensive to control. ANC is achieved by introducing a canceling "anti-noise" wave through an appropriate array of secondary sources. When applied accurately, ANC can provide effective solutions to noise-related problems in a broad range of areas, including manufacturing and industrial operations as well as consumer products. Consequently, ANC research and...
Kernel Adaptive Filtering: A Comprehensive Introduction
Reproducing kernel Hilbert spaces is a topic of great current interest for applications in signal processing, communications, and controls The first book to explain real-time learning algorithms in reproducing kernel Hilbert spaces, On-Line Kernel Learning includes simulations that illustrate the ideas discussed and demonstrate their applicability as well as MATLAB codes for simulations. This book is ideal for professionals and graduate students interested in nonlinear adaptive systems for...
Adaptive Signal Processing: Next Generation Solutions
This book presents the latest research results in adaptive signal processing with an emphasis on important applications and theoretical advancements. Each chapter is self-contained, comprehensive in its coverage, and written by a leader in his or her field of specialty. A uniform style is maintained throughout the book and each chapter concludes with problems for readers to reinforce their understanding of the material presented. The book can be used as a reliable reference for researchers...
Adaptive Filtering: Algorithms and Practical Implementation
This book presents the basic concepts of adaptive signal processing and adaptive filtering in a concise and straightforward manner, using clear notations that facilitate actual implementation. Important algorithms are described in detailed tables which allow the reader to verify learned concepts. The book covers the family of LMS and algorithms as well as set-membership, sub-band, blind, IIR adaptive filtering, and more. The book is also supported by a web page maintained by the author.
Adaptive Filters
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,...
Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches
Focuses on System Identification applications of the adaptive methods presented. but which can also be applied to other applications of adaptive nonlinear processes.
Covers recent research results in the area of adaptive nonlinear system identification from the authors and other researchers in the field.
Adaptive Filtering Primer with MATLAB
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®...
Principles of Adaptive Filters and Self-learning Systems
Teaches students about classical and nonclassical adaptive systems within one pair of covers
Helps tutors with time-saving course plans, ready-made practical assignments and examination guidance
The recently developed "practical sub-space adaptive filter" allows the reader to combine any set of classical and/or non-classical adaptive systems to form a powerful technology for solving complex nonlinear problems
Fundamentals of Adaptive Filtering
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...
Adaptive Filtering: Algorithms and Practical Implementation
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...
Advances in Network and Acoustic Echo Cancellation (Digital Signal Processing (Springer-Verlag).)
This book brings together many advanced topics in network and acoustic echo cancellation aimed towards enhancing the echo cancellation performance of next-generation telecommunication systems. The resulting compendium provides a coherent treatment of such topics not found otherwise in journals or other books.
