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Theoretical Foundations and Numerical Methods for Sparse Recovery

By Massimo Fornasier

Product Image: Theoretical Foundations and Numerical Methods for Sparse Recovery

Theoretical Foundations and Numerical Methods for Sparse Recovery

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Description
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
Product details
Edition:
1
Number of Pages:
352
Release Date:
2010-07-16
Publication Date:
2010-07-16
Publisher:
De Gruyter
Languages:
Original: English
ISBN10:
3110226146
ISBN13:
9783110226140
GPSR Manufacturer Reference:
[email protected]
Weight:
776 g
Height:
175 cm
Width:
246 cm
Thickness:
24 cm
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