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Advanced Concepts in Adaptive Signal Processing / Edition 1

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Overview

This book presents a number of important, but not so well-known, topics that currently exist scattered in the research literature.
Advanced Concepts in Adaptive Signal Processing is intended to serve practitioners who need to consider using advanced techniques that are not found documented in currently available books. This book can also be used as a text in advanced graduate level courses on special topics. As a work that integrates the major results of four recent PhD dissertations, this book represents many man-years of research efforts. The text is rich with illustrative computer-generated examples, many of which were designed to investigate unknown phenomena, rather than to demonstrate already known principles.
Advanced Concepts in Adaptive Signal Processing is written for the reader who is familiar with the conventional field of captive signal processing. A fundamental course from one of the many referenced texts would provide sufficient background. Throughout the book, where it was deemed necessary, certain conventional topics are developed in more detail to provide essential background.

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Editorial Reviews

Booknews
Presents and develops advanced adaptive signal processing concepts that extend the capabilities of the technique beyond the current state of the art. Documents new results in areas including improved performance adaptive algorithms for 1-D adaptive filters, architectures and algorithms for 2-D adaptive filters, the introduction and development of adaptive fault tolerance, and adaptive polynomial filters. Includes a detailed overview chapter introducing the subject, research since the 1950s, and necessary terminology. For engineers and scientists, and graduate students. Annotation c. by Book News, Inc., Portland, Or.
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Product Details

Table of Contents

Preface. 1: Introduction and Background. 1.1. Common Adaptive Concepts from Different Disciplines. 1.2. Generic Applications of Adaptive Methods. 1.3. Performance Measures in Adaptive Systems. 1.4. The Minimum Mean Squared Error Solution. 1.5. Adaptive Algorithms for FIR Systems. 1.6. Adaptive Algorithms for IIR Systems. 1.7. New Horizons in Adaptive Signal Processing. 1.8. Notation and Conventions. 2: Advanced Algorithms for 1-D Adaptive Filtering. 2.2. Data- Reusing LMS Algorithms. 2.3. Orthogonalization by PR Modulation. 2.3. The Gauss-Newton Adaptive Filtering algorithm. 2.4. Block Adaptive IIR Filters Using the PCG Method. 3: Structures and Algorithms for Two-Dimensional Adaptive Signal Processing. 3.1. Applications of Two-Dimensional Adaptive Filtering. 3.2. Two- Dimensional FIR Adaptive Filtering. 3.3. Two-Dimensional IIR Adaptive Filters. 3.4. Two-Dimensional IIR Adaptive Filtering Experiments. 3.5. Uniqueness Characteristics of the 2-D IIR MSE Minimization. 4: Adaptive Fault Tolerance. 4.1. Application of AFT to FIR Adaptive Filters. 4.2. Adaptive Filter Structures. 4.3. A Simple Fault Tolerant FIR Adaptive Filter. 4.4. The Transform Domain FTAF. 4.5. The DFT-Based TDFTAF with the Conjugate Gradient. 4.6. Robust and Practical TDFTAFs. 4.7. Full Fault Tolerance Transforms. 4.8. Discussion. 5: Adaptive Polynomial Filters. 5.1. The Volterra Series. 5.2. Gradient Based Adaptive Volterra Filters. 5.3. RLSSecond-Order Volterra Adaptive Filter. 5.4. LS Lattice Second-Order Volterra Adaptive Filter. 5.5. QR-Based LS Lattice Second Order Volterra Filter. 5.6. The Adaptive Volterra Filter for Gaussian Signals. 5.7. Other Polynomial-Based Nonlinear Adaptive Filters. 5.8. Discussion. Appendix. Subject Index.

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