Accurate signal recovery in quantized compressed sensing
Date of Issue2012
International Conference on Information Fusion (FUSION) (15th : 2012)
School of Electrical and Electronic Engineering
Compressed sensing (CS) studies the recovery of a high dimensional signal from its low dimensional linear measurements under a sparsity prior. This paper is focused on the CS problem with quantized measurements. An algorithm is proposed based on a Bayesian perspective that treats measurement noises and quantization errors separately and allows data saturation. It is shown to improve the recovery accuracy in comparison with existing approaches by numerical simulations.
DRNTU::Engineering::Electrical and electronic engineering
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