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Empirical analysis of the C-value in the conditional inequality of dimension of measurement matrix in compressive sensing

机译:压缩传感中测量矩阵维数不等式中C值的实证分析

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Standard CS (Compressive Sensing) indicates the number of the samples which should be taken from the original signal in the sender to be reconstructed in the receiver is M ≥ CKμ log N. In the inequality, all of the variables can be known except for C. This paper mainly discusses the factors that influence this variable. Our contributions can be concluded into two aspects: firstly, we conclude that the length N and the sparsity K of the original signal are not the main factors that influence C and it is influenced by the type of measurement matrix and reconstruction algorithm; secondly, we provide the lower bound of C which can be used in practice to reconstruct the original signal with high precision.
机译:标准CS(压缩感测)表示应从发送器中的原始信号中获取的要在接收器中重构的样本数量为M≥CKμlogN。在不等式中,除C以外的所有变量都是已知的本文主要讨论影响此变量的因素。我们的贡献可以归结为两个方面:首先,我们得出结论,原始信号的长度N和稀疏性K不是影响C的主要因素,它受测量矩阵类型和重构算法的影响;其次,我们提供了C的下界,可在实践中用于高精度地重构原始信号。

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