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Engineering - Signals & Communication | Adaptive Filtering - Algorithms and Practical Implementation

Adaptive Filtering

Algorithms and Practical Implementation

Diniz, Paulo S.R.

2nd ed. 2002, XXI, 568 p.

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  • About this textbook

  • Presents a concise overview of adaptive filtering, covering as many algorithms as possible in a unified form that avoids repetition and simplifies notation
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 algorithms that really work in a finite-precision implementation, and to provide easy access to working algorithms. Hence, practicing engineers and scientists will also find the book to be an excellent reference.
This second edition contains a substantial amount of new material:

-Two new chapters on nonlinear and subband adaptive filtering;
-Linearly constrained Weiner filters and LMS algorithms;
-LMS algorithm behavior in fast adaptation;
-Affine projection algorithms;
-Derivation smoothing;
-MATLAB codes for algorithms.

Content Level » Professional/practitioner

Keywords » Adaptive Filter - Matlab - Signal - algorithms - communication - filter - filtering - material - micro-alloy transistor - network - power systems - signal processing

Related subjects » Circuits & Systems - Electronics & Electrical Engineering - Image Processing - Signals & Communication

Table of contents 

Preface. 1. Introduction to Adaptive Filtering. 2. Fundamentals of Adaptive Filtering. 3. The Least-Mean-Square (LMS) Algorithm. 4. LMS-Based Algorithms. 5. Conventional RLS Adaptive Filter. 6. Adaptive Lattice-Based RLS Algorithms. 7. Fast Transversal RLS Algorithms. 8. QR-Decomposition-Based RLS Filters. 9. Adaptive IIR Filters. 10. Nonlinear Adaptive Filtering. 11. Subband Adaptive Filters. A. Quantization Effects in the LMS and RLS Algorithms. Index.

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