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中文摘要：
压缩传感理论（Compressive Sensing,CS）以远低于Nyquist采样频率的非适应性测量和优化方法高概率重构信号.本文介绍了CS的基本理论、重构算法,包括贪婪、凸优化方法及我们提出的MBOOMP算法;同时,采用0-1组成的随机信号进行性能比较的模拟实验,结果表明我们的算法优于传统的OMP算法.
英文摘要：
Compressive sensing,by means of the non-adaptive measurements with a well below the Nyquist frequency and optimization methods,reconstruct signal with high probability.In this paper,we introduce the basic theory of compressed sensing and the main reconstruction algorithms,including iterative algorithms as well as our improved MBOOMP algorithm.Meanwhile,the simulation of radom signal which is composed of 0 and 1 are adapted to compare their performance.It is shown that our algorithm is better than typical OMP algorithm.
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