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Performance Evaluation of Finite Sparse Signals for Compressed Sensing Frameworks
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2018/02/01
Online ISSN: 1745-1361
Type of Manuscript: LETTER
Category: Fundamentals of Information Systems
compressed sensing, finite fields, signal recovery, probabilistic decoding,
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In this paper, we consider to develop a recovery algorithm of a sparse signal for a compressed sensing (CS) framework over finite fields. A basic framework of CS for discrete signals rather than continuous signals is established from the linear measurement step to the reconstruction. With predetermined priori distribution of a sparse signal, we reconstruct it by using a message passing algorithm, and evaluate the performance obtained from simulation. We compare our simulation results with the theoretic bounds obtained from probability analysis.