This book gives a comprehensive overview of both the fundamentals of wavelet analysis and related tools, and of the most active recent developments towards applications. It offers a state-of-the-art in several active areas of research where wavelet ideas, or more generally multiresolution ideas have proved particularly effective. The main applications covered are in the numerical analysis of PDEs, and signal and image processing. Recently introduced techniques such as Empirical Mode Decomposition (EMD) and new trends in the recovery of missing data, such as compressed sensing, are also presented. Applications range for the reconstruction of noisy or blurred images, pattern and face recognition, to nonlinear approximation in strongly anisotropic contexts, and to the classification tools based on multifractal analysis
Author(s): Paulo S. R. Diniz (auth.)
Edition: 3rd ed
Publisher: Springer US
Year: 2008
Language: English
Pages: 636
City: New York
Tags: Signal, Image and Speech Processing;Circuits and Systems;Communications Engineering, Networks;Control , Robotics, Mechatronics;Complexity;Electrical Engineering
Front Matter....Pages 1-20
Introduction To Adaptive Filtering....Pages 1-12
Fundamentals of Adaptive Filtering....Pages 1-63
The Least-Mean-Square (LMS) Algorithm....Pages 1-54
Lms-Based Algorithms....Pages 1-63
Conventional Rls Adaptive Filter....Pages 1-36
Data-Selective Adaptive Filtering....Pages 1-57
Adaptive Lattice-Based Rls Algorithms....Pages 1-43
Fast Transversal Rls Algorithms....Pages 1-17
Qr-Decomposition-Based Rls Filters....Pages 1-43
Adaptive Iir Filters....Pages 1-55
Nonlinear Adaptive Filtering....Pages 1-34
Subband Adaptive Filters....Pages 1-51
Blind Adaptive Filtering....Pages 1-33
Back Matter....Pages 1-54
