Title :
Accurate signal recovery in quantized compressed sensing
Author :
Yang, Zai ; Xie, Lihua ; Zhang, Cishen
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Technol., Singapore, Singapore
Abstract :
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.
Keywords :
Bayes methods; compressed sensing; quantisation (signal); signal sampling; Bayesian perspective; data saturation; low dimensional linear measurements; measurement noise; quantization errors; quantized compressed sensing; quantized measurements; recovery accuracy; signal recovery; sparsity prior; Bayesian methods; Noise; Noise measurement; Numerical models; Quantization; Sensors; Vectors;
Conference_Titel :
Information Fusion (FUSION), 2012 15th International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4673-0417-7
Electronic_ISBN :
978-0-9824438-4-2
