Separation-Based Joint Decoding in Compressive Sensing

DSpace/Manakin Repository

Separation-Based Joint Decoding in Compressive Sensing

Citable link to this page

. . . . . .

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:
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

Show full Dublin Core record

This item appears in the following Collection(s)

  • FAS Scholarly Articles [7362]
    Peer reviewed scholarly articles from the Faculty of Arts and Sciences of Harvard University
 
 

Search DASH


Advanced Search
 
 

Submitters