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Theoretical Foundations and Numerical Methods for Sparse Recovery: 9 (Radon Series on Computational and Applied Mathematics, 9) - Hardcover
Book 5 of 28: Radon Series on Computational and Applied Mathematics
Synopsis
The present collection of four lecture notes 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. This unique collection will be of value for a broad community and may serve as a textbook for graduate courses.
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About the Author
Massimo Fornasier, Johann Radon Institute for Computational and Applied Mathematics, Linz, Austria.
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Theoretical Foundations and Numerical Methods for Sparse Recovery
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De Gruyter, De Gruyter Jul 2010, 2010
ISBN 10: 3110226146
ISBN 13: 9783110226140
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 352 pp. Englisch. Seller Inventory # 9783110226140
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Theoretical Foundations and Numerical Methods for Sparse Recovery
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Hardcover. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Massimo Fornasier, Johann Radon Institute for Computational and Applied Mathematics, Linz, Austria. Seller Inventory # 4455461
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Theoretical Foundations and Numerical Methods for Sparse Recovery
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Theoretical Foundations and Numerical Methods for Sparse Recovery
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Theoretical Foundations and Numerical Methods for Sparse Recovery
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Theoretical Foundations and Numerical Methods for Sparse Recovery (Radon Series on Computational and Applied Mathematics, 9)
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Theoretical Foundations and Numerical Methods for Sparse Recovery (eng)
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Theoretical Foundations and Numerical Methods for Sparse Recovery (Radon Series on Computational and Applied Mathematics, 9)
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hardcover. Condition: Acceptable. Connecting readers with great books since 1972. Used textbooks may not include companion materials such as access codes, etc. May have condition issues including wear and notes/highlighting. We ship orders daily and Customer Service is our top priority! Seller Inventory # S_397327092
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Theoretical Foundations and Numerical Methods for Sparse Recovery
Published by
De Gruyter, De Gruyter Jul 2010, 2010
ISBN 10: 3110226146
ISBN 13: 9783110226140
New
Hardcover
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 PockWalter de Gruyter GmbH, Genthiner Strasse 13, 10785 Berlin 352 pp. Englisch. Seller Inventory # 9783110226140
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Theoretical Foundations and Numerical Methods for Sparse Recovery
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 # 9783110226140