Adaptive Filtering

1. Front Matter

   Pages 1-20

   PDF

2. Introduction To Adaptive Filtering

   • Paulo S.R. Diniz

   Pages 1-12

3. Fundamentals of Adaptive Filtering

   • Paulo S.R. Diniz

   Pages 1-63

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

   • Paulo S.R. Diniz

   Pages 1-54

5. Lms-Based Algorithms

   • Paulo S.R. Diniz

   Pages 1-63

6. Conventional Rls Adaptive Filter

   • Paulo S.R. Diniz

   Pages 1-36

7. Data-Selective Adaptive Filtering

   • Paulo S.R. Diniz

   Pages 1-57

8. Adaptive Lattice-Based Rls Algorithms

   • Paulo S.R. Diniz

   Pages 1-43

9. Fast Transversal Rls Algorithms

   • Paulo S.R. Diniz

   Pages 1-17

10. Qr-Decomposition-Based Rls Filters

    • Paulo S.R. Diniz

    Pages 1-43

11. Adaptive Iir Filters

    • Paulo S.R. Diniz

    Pages 1-55

12. Nonlinear Adaptive Filtering

    • Paulo S.R. Diniz

    Pages 1-34

13. Subband Adaptive Filters

    • Paulo S.R. Diniz

    Pages 1-51

14. Blind Adaptive Filtering

    • Paulo S.R. Diniz

    Pages 1-33

15. Back Matter

    Pages 1-54

    PDF

The field of Digital Signal Processing has developed so fast in the last three decades that it can be found in the graduate and undergraduate programs of most universities. This development is related to the increasingly available technologies 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 call 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 four 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 manner. Still today it is possible to observe many research developments in the area of adaptive filtering, particularly addressing specific applications.

• Signal
• algorithm
• filter
• integrated circuit
• micro-alloy transistor
• single-electron transistor
• static-induction transistor
• tables
• complexity

From the reviews of the third edition:

"This text concentrates on studying on-line algorithms, those whose adaptation occurs whenever a new sample of each environment signal is available. … This edition also includes basic introductions to nonlinear adaptive filtering and blind signal processing as natural extensions of the algorithms … . The book is of great importance for digital signal processing undergraduate and graduate courses in universities." (George S. Stavrakakis, Zentralblatt MATH, Vol. 1155, 2009)

"The book titled ‘Adaptive Filtering: Algorithms and Practical Implementation,’ Third Edition, by Paulo S. R. Diniz replaces two previous editions. This new edition has improved significantly upon those two editions. … The book is also very practical. To attest to its suitability as a teaching text, the author has given a number of carefully developed examples which are useful … to students. … Overall, the book is excellent for teaching the subject of adaptive signal processing and enhances the landscape of textbooks on the subject." (Tokunbo Ogunfunmi, IEEE Communications Magazine, October, 2009)

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