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Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/236999
- Accurate signal recovery in quantized compressed sensing
- Yang, Zai; Xie, Lihua; Zhang, Cishen
- 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.
- Publication type
- Conference paper
- Research centre
- Swinburne University of Technology. Faculty of Engineering and Industrial Sciences
- Proceedings of the 15th International Conference on Information Fusion (FUSION 2012), Singapore, 07-12 September 2012, pp. 2531-2536
- Publication year
- Algorithms; Compressed sensing; Quantized measurements; Recovery accuracy; Signal recovery
- 9781467304177, 1467304174
- Publisher URL
- Copyright © 2012 ISIF.
- Peer reviewed