This book is intended to serve as an invaluable reference for anyone concerned with the application of wavelets to signal processing. It has evolved from material used to teach "wavelet signal processing" courses in electrical engineering departments at Massachusetts Institute of Technology and Tel Aviv University, as well as applied mathematics departments at the Courant Institute of New York University and �cole
Polytechnique in Paris.

Provides a broad perspective on the principles and applications of transient signal processing with wavelets
Emphasizes intuitive understanding, while providing the mathematical foundations and description of fast algorithms
Numerous examples of real applications to noise removal, deconvolution, audio and image compression, singularity and edge detection, multifractal analysis, and time-varying frequency measurements
Algorithms and numerical examples are implemented in Wavelab, which is a Matlab toolbox freely available over the Internet
Content is accessible on several level of complexity, depending on the individual reader's needs

New to the Second Edition

Optical flow calculation and video compression algorithms
Image models with bounded variation functions
Bayes and Minimax theories for signal estimation
200 pages rewritten and most illustrations redrawn
More problems and topics for a graduate course in wavelet signal processing, in engineering and applied mathematics

Recensione:

"Mallat has not only written a treatise, but also an excellent graduate text for students in computer science, electrical engineering, and mathematics" --John J. Benedetto, SIAM review

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Mallat, Stephane

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