Titlebook: Computational Signal Processing with Wavelets; Anthony Teolis Book 2017 Springer International Publishing AG 2017 Applied Signal Processin

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Wavelet Signal Processing,racterized by their time-frequency behavior. This chapter explores applications of overcomplete wavelet transforms in problems of data compression, noise suppression, digital communication, and signal identification.

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2197-1803 tically rigorous while maintaining contact with interesting This unique resource examines the conceptual, computational, and practical aspects of applied signal processing using wavelets.? With this book, readers will understand and be able to use the power and utility of new wavelet methods in scie

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Sudeep Chhabra,Ivan Coste-Manière It is a main objective of this work to strike a balance between accessibility and mathematical rigor that sacrifices as little as possible of both. To help achieve this goal, the dissemination of the material is provided by a hybrid combination of traditional (text) and nontraditional (Internet and electronic) media.

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Introduction, It is a main objective of this work to strike a balance between accessibility and mathematical rigor that sacrifices as little as possible of both. To help achieve this goal, the dissemination of the material is provided by a hybrid combination of traditional (text) and nontraditional (Internet and electronic) media.

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Introduction,ailable. Much of this work, however, requires a fairly in-depth knowledge of several areas of advanced mathematics and hence limits its accessibility. It is a main objective of this work to strike a balance between accessibility and mathematical rigor that sacrifices as little as possible of both. T

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mathematical Premilinaries,elopment of the material. It is meant more as a reference and index of notation than a comprehensive mathematical introduction. Most of the basic notation and concepts that are used may be found in standard texts on real analysis ([Roy68], [Ben76]), operator theory ([GG80]), and discrete signal proc

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