A wavelet tour of signal processing: the sparse way / Stéphane Mallat

Auteur: Mallat, Stéphane (1962-) - AuteurAuteur secondaire : Peyre, Gabriel (1979-) - CollaborateurType de document: MonographieLangue: anglaisPays: Etats UnisÉditeur: Boston : Academic Press, cop. 2009Edition: 3rd editionDescription: 1 vol. (XX-805 p.) : ill. ; 25 cm ISBN: 9780123743701 ; rel. Note: ... This book consists of 13 chapters, an appendix (on mathematical complements), an updated bibliography (with 501 references), and a subject index. Putting sparsity at the center of the book implied rewriting many parts and adding sections. Chapter 1 provides the main ideas and gives an orientation of this book. The titles of Chapters 2–9 are not changed. Chapter 10 introduces the signal compression together with the image compression standards JPEG and JPEG-2000. Chapter 11 presents methods for signal denoising. Chapters 12 and 13 are completely new. Chapter 12 introduces sparse signal approximations in redundant dictionaries with pursuit algorithms. Chapter 13 deals with the resolution of inverse problems, super-resolution, compressive sensing, and source separation. Further new topics in this book are computer tomography, lifting for wavelets on surfaces, geometric image processing with curvelets and bandlets, time-frequency audio processing and denoising. More exercises (ordered by level of difficulty) have been added at the end of each chapter. A new website http://wavelet-tour.com provides exercise solutions, figures, MATLAB toolboxes, C/C++ codes and teaching material (slides with figures). The author proposes 6 course programs which can be covered by selected chapters. This survey of the basic features of most topics of sparse signal processing is an invaluable resource for researchers and graduate students in applied mathematics and signal processing. Without doubt, this work will stimulate the further research. (zbMath)Bibliographie: Bibliogr. p. 765-793. Index. Sujets MSC: 94A12 Information and communication, circuits -- Communication, information -- Signal theory (characterization, reconstruction, filtering, etc.)
94-02 Information and communication, circuits -- Research exposition (monographs, survey articles)
42C40 Harmonic analysis on Euclidean spaces -- Nontrigonometric harmonic analysis -- Wavelets and other special systems
65T60 Numerical analysis -- Numerical methods in Fourier analysis -- Wavelets
94A08 Information and communication, circuits -- Communication, information -- Image processing (compression, reconstruction, etc.)
En-ligne: MathSciNet | zbMath
Location Call Number Status Date Due
Salle R 10582-01 / 94 MAL (Browse Shelf) Available

... This book consists of 13 chapters, an appendix (on mathematical complements), an updated bibliography (with 501 references), and a subject index. Putting sparsity at the center of the book implied rewriting many parts and adding sections. Chapter 1 provides the main ideas and gives an orientation of this book. The titles of Chapters 2–9 are not changed. Chapter 10 introduces the signal compression together with the image compression standards JPEG and JPEG-2000. Chapter 11 presents methods for signal denoising. Chapters 12 and 13 are completely new. Chapter 12 introduces sparse signal approximations in redundant dictionaries with pursuit algorithms. Chapter 13 deals with the resolution of inverse problems, super-resolution, compressive sensing, and source separation. Further new topics in this book are computer tomography, lifting for wavelets on surfaces, geometric image processing with curvelets and bandlets, time-frequency audio processing and denoising.

More exercises (ordered by level of difficulty) have been added at the end of each chapter. A new website http://wavelet-tour.com provides exercise solutions, figures, MATLAB toolboxes, C/C++ codes and teaching material (slides with figures). The author proposes 6 course programs which can be covered by selected chapters. This survey of the basic features of most topics of sparse signal processing is an invaluable resource for researchers and graduate students in applied mathematics and signal processing. Without doubt, this work will stimulate the further research. (zbMath)

Bibliogr. p. 765-793. Index

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