Performance evaluation of finite sparse signals for compressed sensing frameworks

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Abstract

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.

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APA

Seong, J. T. (2018). Performance evaluation of finite sparse signals for compressed sensing frameworks. IEICE Transactions on Information and Systems, E101D(2), 531–534. https://doi.org/10.1587/transinf.2017EDL8166

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