Accurate signal recovery in quantized compressed sensing

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...

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Main Authors: Yang, Zai, Xie, Lihua, Zhang, Cishen
Other Authors: School of Electrical and Electronic Engineering
Format: Conference Paper
Language:English
Published: 2014
Subjects:
Online Access:https://hdl.handle.net/10356/101861
http://hdl.handle.net/10220/19739
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6290462
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author Yang, Zai
Xie, Lihua
Zhang, Cishen
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Yang, Zai
Xie, Lihua
Zhang, Cishen
author_sort Yang, Zai
collection NTU
description 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.
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spelling ntu-10356/1018612019-12-06T20:45:54Z Accurate signal recovery in quantized compressed sensing Yang, Zai Xie, Lihua Zhang, Cishen School of Electrical and Electronic Engineering International Conference on Information Fusion (FUSION) (15th : 2012) DRNTU::Engineering::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. Published version 2014-06-13T03:21:02Z 2019-12-06T20:45:54Z 2014-06-13T03:21:02Z 2019-12-06T20:45:54Z 2012 2012 Conference Paper Yang, Z., Xie, L., & Zhang, C. (2012). Accurate signal recovery in quantized compressed sensing. 2012 15th International Conference on Information Fusion (FUSION), 2531-2536. https://hdl.handle.net/10356/101861 http://hdl.handle.net/10220/19739 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6290462 en © 2012 International Society of Information Fusion. This paper was published in 2012 15th International Conference on Information Fusion (FUSION) and is made available as an electronic reprint (preprint) with permission of International Society of Information Fusion. The paper can be found at the following official URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6290462. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law. application/pdf
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Yang, Zai
Xie, Lihua
Zhang, Cishen
Accurate signal recovery in quantized compressed sensing
title Accurate signal recovery in quantized compressed sensing
title_full Accurate signal recovery in quantized compressed sensing
title_fullStr Accurate signal recovery in quantized compressed sensing
title_full_unstemmed Accurate signal recovery in quantized compressed sensing
title_short Accurate signal recovery in quantized compressed sensing
title_sort accurate signal recovery in quantized compressed sensing
topic DRNTU::Engineering::Electrical and electronic engineering
url https://hdl.handle.net/10356/101861
http://hdl.handle.net/10220/19739
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6290462
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AT zhangcishen accuratesignalrecoveryinquantizedcompressedsensing