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Compressed sensing : theory and applications

Author: Yonina C Eldar; Gitta Kutyniok
Publisher: Cambridge ; New York : Cambridge University Press, 2012.
Edition/Format:   Print book : EnglishView all editions and formats
"Compressed sensing is an exciting, rapidly growing field, attracting considerable attention in electrical engineering, applied mathematics, statistics and computer science. This book provides the first detailed introduction to the subject, highlighting recent theoretical advances and a range of applications, as well as outlining numerous remaining research challenges. After a thorough review of the basic theory,  Read more...
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Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: Yonina C Eldar; Gitta Kutyniok
ISBN: 9781107005587 1107005582
OCLC Number: 756578482
Description: xii, 544 pages : illustrations ; 26 cm
Contents: 1. Introduction to compressed sensing / Mark A. Davenport, Marco F. Duarte, Yonina C. Eldar, and Gitta Kutyniok --
2. Second-generation sparse modeling : structured and collaborative signal analysis / Alexey Castrodad, Ignacio Ramirez, Guillermo Sapiro, Pablo Sprechmann, and Guoshen Yu --
3. Xampling : compressed sensing of analog signals / Moshe Mishali and Yonina C. Eldar --
4. Sampling at the rate of innovation : theory and applications / Jose Antonia Urigüen, Yonina C. Eldar, Pier Luigi Dragotta, and Zvika Ben-Haim --
5. Introduction to the non-asymptotic analysis of random matrices / Roman Vershynin --
6. Adaptive sensing for sparse recovery / Jarvis Haupt and Robert Nowak --
7. Fundamental thresholds in compressed sensing : a high-dimensional geometry approach / Weiyu Xu and Babak Hassibi --
8. Greedy algorithms for compressed sensing / Thomas Blumensath, Michael E. Davies, and Gabriel Rilling --
9. Graphical models concepts in compressed sensing / Andrea Montanari --
10. Finding needles in compressed haystacks / Robert Calderbank and Sina Jafarpour --
11. Data separation by sparse representations / Gitta Kutyniok --
12. Face recognition by sparse representation / Arvind Ganesh, Andrew Wagner, Zihan Zhou, Allen Y. Yang, Yi Ma, and John Wright.
Responsibility: edited by Yonina C. Eldar, Gitta Kutyniok.


A detailed presentation of compressed sensing by leading researchers, covering the most significant theoretical and application-oriented advances.  Read more...
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'... a charming encouragement to fascinating scientific adventure for talented students. Also ... a solid reference platform for researchers in many fields.' Artur Przelaskowski, IEEE Communications Read more...

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