Row-Action Methods for Compressed Sensing
2006
Conference Paper
ei
Compressed Sensing uses a small number of random, linear measurements to acquire a sparse signal. Nonlinear algorithms, such as l1 minimization, are used to reconstruct the signal from the measured data. This paper proposes rowaction methods as a computational approach to solving the l1 optimization problem. This paper presents a specific rowaction method and provides extensive empirical evidence that it is an effective technique for signal reconstruction. This approach offers several advantages over interior-point methods, including minimal storage and computational requirements, scalability, and robustness.
Author(s): | Sra, S. and Tropp, J. |
Book Title: | ICASSP 2006 |
Journal: | Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006) |
Pages: | 868-871 |
Year: | 2006 |
Month: | May |
Day: | 0 |
Publisher: | IEEE Operations Center |
Department(s): | Empirical Inference |
Bibtex Type: | Conference Paper (inproceedings) |
DOI: | 10.1109/ICASSP.2006.1660792 |
Event Name: | IEEE International Conference on Acoustics, Speech and Signal Processing |
Event Place: | Toulouse, France |
Address: | Piscataway, NJ, USA |
Digital: | 0 |
Language: | en |
Organization: | Max-Planck-Gesellschaft |
School: | Biologische Kybernetik |
Links: |
Web
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BibTex @inproceedings{5222, title = {Row-Action Methods for Compressed Sensing}, author = {Sra, S. and Tropp, J.}, journal = {Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006)}, booktitle = {ICASSP 2006}, pages = {868-871}, publisher = {IEEE Operations Center}, organization = {Max-Planck-Gesellschaft}, school = {Biologische Kybernetik}, address = {Piscataway, NJ, USA}, month = may, year = {2006}, doi = {10.1109/ICASSP.2006.1660792}, month_numeric = {5} } |