Theoretical Foundations and Numerical Methods for Sparse Recovery
Language: English
Published by De Gruyter, DE, 2010
Series: Book 5 of 28 - Radon Series on Computational and Applied Mathematics
- Hardcover
- New
Seller: Rarewaves USA, HEBRON, KY, U.S.A.Rarewaves USA
AbeBooks seller since June 10, 2025
Condition: New
US$ 363.16
Quantity: Over 20 available
Add to basketItem description from seller
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.…
Seller Inventory # LU-9783110226140
- Title
- Theoretical Foundations and Numerical Methods for Sparse Recovery
- Author
- Massimo Fornasier
- Publisher
- De Gruyter, DE
- Publication year
- 2010
- Condition
- New
- Binding
- Hardback
- Language
- English
- ISBN 10
- 3110226146
- ISBN 13
- 9783110226140
- Item weight
- 730 grams
- Series
- Book 5 of 28: Radon Series on Computational and Applied Mathematics
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
"Synopsis" may belong to another edition of this title.
About the Author
Massimo Fornasier, Johann Radon Institute for Computational and Applied Mathematics, Linz, Austria.
"About the title" may belong to another edition of this title.
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