压缩感知理论与应用
压缩感知理论与应用全书，共12章，各章标题如下：
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 Uriguen, 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, Sina Jafarpour and Jeremy Kent;
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.
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本站所有资源不代表本站的观点或立场，基于网友分享，根据中国法律《信息网络传播权保护条例》第二十二条之规定，若资源存在侵权或相关问题请联系本站客服人员，zhiweidada#qq.com，请把#换成@，本站将给予最大的支持与配合，做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明