Robust GNC approach for quantised compressed sensing
Author | Elleuch, I. |
Author | Abdelkefi, F. |
Author | Siala, M. |
Author | Hamila, R. |
Author | Al-Dahir, N. |
Available date | 2020-11-19T08:53:09Z |
Publication Date | 2017 |
Publication Name | Electronics Letters |
Resource | Scopus |
ISSN | 135194 |
Abstract | Practical acquisition of compressed sensing measurements involves a finite-range finite-precision quantisation step. To solve the sparse recovery problem and handle the quantisation distortion, this Letter proposes a non-smooth graduated-non-convexity approach that follows a path of gradually improved solutions along a sequence of non-smooth non-convex optimisation problems that progressively promote quantisation consistency (QC) and sparsity. We consider two classes of multi-scale continuous approximation functions to depict intermediate QC degrees and sparsity-inducing strengths, respectively, and apply recent proximal splitting methods to solve the resulting subproblem at each refinement scale. The simulations demonstrate the convergence of intermediate solutions to a nearly optimal estimation, in terms of accuracy and support recovery. |
Language | en |
Publisher | Institution of Engineering and Technology |
Subject | Compressed Sensing Bits Quantization |
Type | Article |
Pagination | 1306-1308 |
Issue Number | 19 |
Volume Number | 53 |
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Electrical Engineering [2495 items ]