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Theoretical Foundations and Numerical Methods for Sparse Recovery
Hardcover
Series: Radon Computational and Applied Mathematics, Book 9
ISBN13: 9783110226140
Publisher: De Gruyter
Published: Jul 16 2010
Pages: 350
Weight: 1.60
Height: 1.00 Width: 6.90 Depth: 9.60
Language: English
The present collection is the very first contribution of this type in the field of sparse recovery. Compressed sensing is one of the important facets of the broader concept presented in the book, which by now has made connections with other branches such as mathematical imaging, inverse problems, numerical analysis and simulation.
The book consists of four lecture notes of courses given at the Summer School on Theoretical Foundations and Numerical Methods for Sparse Recovery held at the Johann Radon Institute for Computational and Applied Mathematics in Linz, Austria, in September 2009. This unique collection will be of value for a broad community and may serve as a textbook for graduate courses.
From the contents:
Compressive Sensing and Structured Random Matrices by Holger Rauhut
Numerical Methods for Sparse Recovery by Massimo Fornasier
Sparse Recovery in Inverse Problems by Ronny Ramlau and Gerd Teschke
An Introduction to Total Variation for Image Analysis by Antonin Chambolle, Vicent Caselles, Daniel Cremers, Matteo Novaga and Thomas Pock
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