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QRD-RLS Adaptive Filtering

  • Book
  • © 2009

Overview

Editors:
  1. José Antonio Apolinário
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  • Provides a comprehensive framework of QRD-RLS adaptive filtering

  • Compiles the research of more than a decade into a single publication

  • Includes an important class of algorithms that are efficient in terms of speed of convergence, computational complexity, and numerical stability

  • Covers algorithms for many scenarios such as single channel, multichannel, and output filtering

  • Includes supplementary material: sn.pub/extras

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Table of contents (12 chapters)

  1. Front Matter

    Pages 1-17
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  2. QR Decomposition An Annotated Bibliography

    • Marcello L.R. de Campos, Gilbert Strang
    Pages 1-22

  3. Introduction to Adaptive Filters

    • José A. Apolinário Jr, Sergio L. Netto
    Pages 1-27

  4. Conventional and Inverse QRD-RLS Algorithms

    • José A. Apolinário Jr, Maria D. Miranda
    Pages 1-35

  5. Fast QRD-RLS Algorithms

    • José A. Apolinário Jr, Paulo S.R. Diniz
    Pages 1-27

  6. QRD Least-Squares Lattice Algorithms

    • Jenq-Tay Yuan
    Pages 1-31

  7. Multichannel Fast QRD-RLS Algorithms

    • António L. L. Ramos, Stefan Werner
    Pages 1-34

  8. Householder-Based RLS Algorithms

    • Athanasios A. Rontogiannis, Sergios Theodoridis
    Pages 1-23

  9. Numerical Stability Properties

    • Phillip Regalia, Richard Le Borne
    Pages 1-29

  10. Finite and Infinite-Precision Properties of QRD-RLS Algorithms

    • Paulo S.R. Diniz, Marcio G. Siqueira
    Pages 1-33

  11. On Pipelined Implementations of QRD-RLS Adaptive Filters

    • Jun Ma, Keshab K. Parhi
    Pages 1-29

  12. Weight Extraction of Fast QRD-RLS Algorithms

    • Stefan Werner, Mohammed Mobien
    Pages 1-24

  13. Linear Constrained QRD-Based Algorithm

    • Shiunn-Jang Chern
    Pages 1-23

  14. Back Matter

    Pages 1-4
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Keywords

About this book

I feel very honoured to have been asked to write a brief foreword for this book on QRD-RLS Adaptive Filtering–asubjectwhichhas been close to my heart for many years. The book is well written and very timely – I look forward personally to seeing it in print. The editor is to be congratulated on assembling such a highly esteemed team of contributing authors able to span the broad range of topics and concepts which underpin this subject. In many respects, and for reasons well expounded by the authors, the LMS al- rithm has reigned supreme since its inception, as the algorithm of choice for prac- cal applications of adaptive ltering. However, as a result of the relentless advances in electronic technology, the demand for stable and ef cient RLS algorithms is growing rapidly – not just because the higher computational load is no longer such a serious barrier, but also because the technological pull has grown much stronger in the modern commercial world of 3G mobile communications, cognitive radio, high speed imagery, and so on.

Reviews

From the reviews:

“Starting with a review of the history and the essential concepts in (numerical) linear algebra that are essential in the development of QR decomposition, the book continues with an overview of adaptive filtering techniques, including LMS and RLS algorithms. … The chapters flow on nicely from one to the other, and the editor is to be congratulated on achieving this. The book is a useful and welcome contribution to the broad topic of numerical linear algebra.” (Andrew Dale, Zentralblatt MATH, Vol. 1170, 2009)

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