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Principles of Adaptive Filters and Self-learning Systems

  • Textbook
  • © 2005

Overview

Authors:
  1. Anthony Zaknich

    1. School of Engineering Science, Rockingham Campus, Murdoch University, Murdoch, Australia
      Centre for Intelligent Information Processing Systems, School of Electrical, Electronic and Computer Engineering, The University of Western Australia, Crawley, Australia

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Editors:
  1. Michael J. Grimble

    1. Industrial Control Centre, Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, UK

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  2. Michael A. Johnson

    1. Industrial Control Centre, Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, UK

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  • 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
  • Includes supplementary material: sn.pub/extras
  • Request lecturer material: sn.pub/lecturer-material

Part of the book series: Advanced Textbooks in Control and Signal Processing (C&SP)

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Table of contents (16 chapters)

  1. Front Matter

    Pages i-xxii
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  2. Introduction

    1. Adaptive Filtering

      Pages 3-23

    2. Linear Systems and Stochastic Processes

      Pages 25-85

  4. Classical Filters and Spectral Analysis

    1. Optimum Wiener Filter

      Pages 159-172

    2. Optimum Kalman Filter

      Pages 173-195

    3. Power Spectral Density Analysis

      Pages 197-224

  5. Adaptive Filter Theory

    1. Adaptive Finite Impulse Response Filters

      Pages 227-245

    2. Frequency Domain Adaptive Filters

      Pages 247-256

    3. Adaptive Volterra Filters

      Pages 257-265

    4. Adaptive Control Systems

      Pages 267-285

  6. Nonclassical Adaptive Systems

    1. Introduction to Neural Networks

      Pages 289-311

    2. Introduction to Fuzzy Logic Systems

      Pages 313-324

    3. Introduction to Genetic Algorithms

      Pages 325-336

  7. Adaptive Filter Application

    1. Applications of Adaptive Signal Processing

      Pages 339-353

    2. Generic Adaptive Filter Structures

      Pages 355-371

  8. Back Matter

    Pages 373-386
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Keywords

About this book

The topics of control engineering and signal processing continue to flourish and develop. In common with general scientific investigation, new ideas, concepts and interpretations emerge quite spontaneously and these are then discussed, used, discarded or subsumed into the prevailing subject paradigm. Sometimes these innovative concepts coalesce into a new sub-discipline within the broad subject tapestry of control and signal processing. This preliminary battle between old and new usually takes place at conferences, through the Internet and in the journals of the discipline. After a little more maturity has been acquired by the new concepts then archival publication as a scientific or engineering monograph may occur. A new concept in control and signal processing is known to have arrived when sufficient material has evolved for the topic to be taught as a specialised tutorial workshop or as a course to undergraduate, graduate or industrial engineers. Advanced Textbooks in Control and Signal Processing are designed as a vehicle for the systematic presentation of course material for both popular and innovative topics in the discipline. It is hoped that prospective authors will welcome the opportunity to publish a structured and systematic presentation of some of the newer emerging control and signal processing technologies in the textbook series.

Reviews

From the reviews:

"An excellent tutorial for graduate students and a comprehensive introduction for researchers working in adaptive systems. Summing Up: Highly Recommended."
(J. Y. Cheung, Choice, February, 2006)

Authors, Editors and Affiliations

  • Industrial Control Centre, Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, UK

    Michael J. Grimble, Michael A. Johnson

  • School of Engineering Science, Rockingham Campus, Murdoch University, Murdoch, Australia

    Anthony Zaknich

  • Centre for Intelligent Information Processing Systems, School of Electrical, Electronic and Computer Engineering, The University of Western Australia, Crawley, Australia

    Anthony Zaknich

About the editors

Anthony Zaknich (M'87-'00) was born in Vela Luka, Croatia, and immigrated to Australia in the 1950s. He received the B.E. (Electronics) and M.E.Sc. degrees from the University of Western Australia (UWA), Nedlands in 1974 and 1986, respectively; the B.A. and B.Sc. (Psychology) degrees from Ambassador University, Pasadena, CA, USA, both in 1978; and the Ph.D. degree from UWA in 1996.

He is currently an Adjunct Associate Professor at UWA, Centre for Intelligent Information Processing Systems (CIIPS) and also at Murdoch University, Perth Western Australia (Division of Science and Engineering). From 1990 to 1999 he held the position of Technical Manager for Industry Projects working as a Research Fellow and Lecturer at CIIPS in the Electrical and Electronics Engineering Department, UWA. His main work at CIIPS was involved with supervision, teaching, research and development related to signal processing and artificial neural networks at the undergraduate, postgraduate and professional-development levels. Previously, he was involved in the research and development of underwater control and acoustic signalling systems in private enterprise, and also in the establishment of a public company, Nautronix Ltd, producing and marketing products in these areas for the international market. He has supervised numerous Honours and ten postgraduate research projects, including three Ph.Ds. He has also authored/co-authored more than 56 refereed papers in technical journals and conference proceedings, has contributed five research book chapters, and authored two books in his areas of interest since 1988. His special research interest is related to integrated sensory-intelligent systems (ISIS): The philosophy, theory and applications of, intelligent signal processing; learning theory; self-learning systems; artificial neural networks; adaptive systems; time-frequency filters and signal analysis; time delay spectrometry; adaptive space-time-frequency signal processing; audio andHi-Fi, and underwater acoustic communications systems.

Dr Zaknich is a Member of the Audio Engineering Society (AES). He served on the IEEE Western Australian Regional Interest Group Committee on Neural Networks at various times since 1993. In 1998 he won the 1996-98, UWA Electrical and Electronics Engineering Department's Outstanding Early Researcher Award, which is given to the best researcher below Senior Lecturer level over any three year period.

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