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Adaptive Filtering

Algorithms and Practical Implementation

  • Book
  • © 1997

Overview

Authors:
  1. Paulo Sergio Ramirez Diniz

    1. Federal University of Rio de Janeiro, Brazil

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Part of the book series: The Springer International Series in Engineering and Computer Science (SECS, volume 399)

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Table of contents (9 chapters)

  1. Front Matter

    Pages i-xv
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  2. Introduction to Adaptive Filtering

    • Paulo Sergio Ramirez Diniz
    Pages 1-14

  3. Fundamentals of Adaptive Filtering

    • Paulo Sergio Ramirez Diniz
    Pages 15-69

  4. The Least-Mean-Square (LMS) Algorithm

    • Paulo Sergio Ramirez Diniz
    Pages 71-131

  5. LMS-Based Algorithms

    • Paulo Sergio Ramirez Diniz
    Pages 133-181

  6. Conventional RLS Adaptive Filter

    • Paulo Sergio Ramirez Diniz
    Pages 183-236

  7. Adaptive Lattice-Based RLS Algorithms

    • Paulo Sergio Ramirez Diniz
    Pages 237-287

  8. Fast Transversal RLS Algorithms

    • Paulo Sergio Ramirez Diniz
    Pages 289-309

  9. QR-Decomposition-Based RLS Filters

    • Paulo Sergio Ramirez Diniz
    Pages 311-376

  10. Adaptive IIR Filters

    • Paulo Sergio Ramirez Diniz
    Pages 377-436

  11. Back Matter

    Pages 437-443
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Keywords

About this book

The field of Digital Signal Processing has developed so fast in the last two decades that it can be found in the graduate and undergraduate programs of most universities. This development is related to the growing available techno­ logies for implementing digital signal processing algorithms. The tremendous growth of development in the digital signal processing area has turned some of its specialized areas into fields themselves. If accurate information of the signals to be processed is available, the designer can easily choose the most appropriate algorithm to process the signal. When dealing with signals whose statistical properties are unknown, fixed algorithms do not process these signals efficiently. The solution is to use an adaptive filter that automatically changes its characteristics by optimizing the internal parameters. The adaptive filtering algorithms are essential in many statistical signal processing applications. Although the field of adaptive signal processing has been subject of research for over three decades, it was in the eighties that a major growth occurred in research and applications. Two main reasons can be credited to this growth, the availability of implementation tools and the appearance of early textbooks exposing the subject in an organized form. Presently, there is still a lot of activities going on in the area of adaptive filtering. In spite of that, the theor­ etical development in the linear-adaptive-filtering area reached a maturity that justifies a text treating the various methods in a unified way, emphasizing the algorithms that work well in practical implementation.

Authors and Affiliations

  • Federal University of Rio de Janeiro, Brazil

    Paulo Sergio Ramirez Diniz

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