Two-Part Reconstruction in Compressed Sensing

Authors

Yanting Ma, North Carolina State University at Raleigh
Dror Baron, North Carolina State University at Raleigh
Deanna Needell, Claremont McKenna CollegeFollow

Document Type

Article - preprint

Department

Mathematics (CMC)

Publication Date

9-11-2013

Abstract

Two-part reconstruction is a framework for signal recovery in compressed sensing (CS), in which the advantages of two different algorithms are combined. Our framework allow s to accelerate the reconstruction procedure without compromising the reconstruction quality. To illustrate the efficacy of ou r two-part approach, we extend the author’s previous Sudocodes algorithm and make it robust to measurement noise. In a 1- bit CS setting, promising numerical results indicate that our algorithm offers both a reduction in run-time and improvement in reconstruction quality

Rights Information

© 2013 Ma, Baron, Needell

Terms of Use & License Information

Terms of Use for work posted in Scholarship@Claremont.

Recommended Citation

Ma, Y., Baron, D., Needell, D., "Two-Part Reconstruction in Compressed Sensing", Submitted, arXiv preprint arXiv:1306.5776, 2013.