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Received:September 11, 2013 Revised:October 16, 2013
Received:September 11, 2013 Revised:October 16, 2013
中文摘要: 本文提出了基于贝叶斯压缩感知的信号重构算法,将压缩感知理论应用于信号的压缩传输以及重构,该算法将压缩感知问题转化为线性回归问题,逐步推演出结果向量之间的迭代关系,最后通过迭代以得到原始信号的精确重构. 仿真说明了贝叶斯压缩感知在信号处理中的应用,结果表明该算法对一维和二维信号的压缩重构有很好的效果.
Abstract:In this paper, a compressed sensing signal reconstruction algorithm that based on Bayesian compression perception theory is proposed. It can be applied to signal compression and transmission as well as reconstruction. The new algorithm inverted the compressed sensing problem into a linear regression problem. Firstly, then deduced an iterative relationship of the resulting vectors gradually, at last got the exact reconstruction of the original signal by iteration. The simulation experiment exploted that the Bayesian compressive sensing algorithm have a good reconstruction effect used in one-dimensional and two-dimensional signal processing and the reconstruction.
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基金项目:上海师范大学创新性和前瞻性项目(DYL.201007);国家自然科学基金(60971004)
引用文本:
陆海东,顾美康,申晓磊.基于贝叶斯压缩感知的信号重构.计算机系统应用,2014,23(5):95-100
LU Hai-Dong,GU Mei-Kang,SHEN Xiao-Lei.Signal Reconstruction Based on Bayesian Compression Sensing.COMPUTER SYSTEMS APPLICATIONS,2014,23(5):95-100
陆海东,顾美康,申晓磊.基于贝叶斯压缩感知的信号重构.计算机系统应用,2014,23(5):95-100
LU Hai-Dong,GU Mei-Kang,SHEN Xiao-Lei.Signal Reconstruction Based on Bayesian Compression Sensing.COMPUTER SYSTEMS APPLICATIONS,2014,23(5):95-100