Retrieve Sparse Solution of Multiple-Measurement Vectors via Zero-point Attracting Projection

Details Retrieve Sparse Solution of Multiple-Measurement Vectors via Zero-point Attracting Projection Retrieve Sparse Solution of Multiple-Measurement Vectors via Zero-point Attracting Projection

2012-03-07

arxiv.org/abs/1203.1548v1

Computer Science

Information Theory

12 pages, 4 figures

Scientific paper

A new sparse signal recovery algorithm for multiple-measurement vectors (MMV) problem is proposed in this paper. The sparse representation is iteratively drawn based on the idea of zero-point attracting projection (ZAP). In each iteration, the solution is first updated along the negative gradient direction of sparse constraint, and then projected to the solution space to satisfy the under-determined equation. A variable step size scheme is adopted further to accelerate the convergence as well as to improve the recovery accuracy. Numerical simulations demonstrate that the performance of the proposed algorithm exceeds the references in various aspects, as well as when applied to the Modulated Wideband Converter, where recovering MMV problem is crucial to its performance.

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