压缩感知理论与应用资源下载
资源描述
本仓库提供了一本名为《压缩感知理论与应用》的全书资源下载。该书共包含12章，涵盖了压缩感知理论及其在各个领域的应用。以下是各章节的标题：
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Introduction to compressed sensing
Mark A. Davenport, Marco F. Duarte, Yonina C. Eldar, and Gitta Kutyniok -
Second generation sparse modeling: structured and collaborative signal analysis
Alexey Castrodad, Ignacio Ramirez, Guillermo Sapiro, Pablo Sprechmann, and Guoshen Yu -
Xampling: compressed sensing of analog signals
Moshe Mishali and Yonina C. Eldar -
Sampling at the rate of innovation: theory and applications
Jose Antonia Uriguen, Yonina C. Eldar, Pier Luigi Dragotta, and Zvika Ben-Haim -
Introduction to the non-asymptotic analysis of random matrices
Roman Vershynin -
Adaptive sensing for sparse recovery
Jarvis Haupt and Robert Nowak -
Fundamental thresholds in compressed sensing: a high-dimensional geometry approach
Weiyu Xu and Babak Hassibi -
Greedy algorithms for compressed sensing
Thomas Blumensath, Michael E. Davies, and Gabriel Rilling -
Graphical models concepts in compressed sensing
Andrea Montanari -
Finding needles in compressed haystacks
Robert Calderbank, Sina Jafarpour, and Jeremy Kent -
Data separation by sparse representations
Gitta Kutyniok -
Face recognition by sparse representation
Arvind Ganesh, Andrew Wagner, Zihan Zhou, Allen Y. Yang, Yi Ma, and John Wright
使用说明
- 下载资源：点击仓库中的资源文件进行下载。
- 阅读方式：建议使用PDF阅读器打开文件进行阅读。
- 内容概览：各章节详细介绍了压缩感知理论及其在不同领域的应用，适合对压缩感知感兴趣的研究人员和学生阅读。
注意事项
- 请尊重版权，仅限个人学习和研究使用。
- 如有任何问题或建议，欢迎通过仓库的Issues功能提出。
希望这份资源能够帮助你更好地理解和应用压缩感知理论！