基于贝叶斯压缩感知的信号重构  

Signal Reconstruction Based on Bayesian Compression Sensing

作　　者：陆海东[1] 顾美康[1] 申晓磊[2] 

机构地区：[1]上海师范大学信息与机电工程学院,上海200234 [2]东华大学信息科学与技术学院,上海200050

出　　处：《计算机系统应用》2014年第5期95-100,共6页Computer Systems & Applications

基　　金：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)

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.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.

关 键 词：贝叶斯 压缩感知 BCS算法 信号重构 

分 类 号：TN911.7[电子电信—通信与信息系统]