Separation-Based Joint Decoding in Compressive Sensing
| Title: | Separation-Based Joint Decoding in Compressive Sensing |
| Author: |
Kung, H.T. T.; Chen, Kevin
Note: Order does not necessarily reflect citation order of authors. |
| Citation: | Chen, Hsieh-Chung and H.T. Kung. 2011. Separation-based joint decoding in compressive sensing. In 2011 Proceedings of 20th International Conference on Computer Communications and Networks (ICCCN 2011), 1-6. Piscataway, New Jersey: IEEE Communications Society. |
| Full Text & Related Files: |
2011-icccn-chen-kung-1.pdf (996.9Kb; PDF) 
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| Abstract: | We introduce a joint decoding method for compressive sensing that can simultaneously exploit sparsity of individual components of a composite signal. Our method can significantly reduce the total number of variables decoded jointly by separating variables of large magnitudes in one domain and using only these variables to represent the domain. Furthermore, we enhance the separation accuracy by using joint decoding across multiple domains iteratively. This separation-based approach improves the decoding time and quality of the recovered signal. We demonstrate these benefits analytically and by presenting empirical results. |
| Published Version: | doi:10.1109/ICCCN.2011.6005915 |
| Terms of Use: | This article is made available under the terms and conditions applicable to Open Access Policy Articles, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#OAP |
| Citable link to this page: | http://nrs.harvard.edu/urn-3:HUL.InstRepos:10021421 |
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Peer reviewed scholarly articles from the Faculty of Arts and Sciences of Harvard University
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