一类新的盲反褶积判据

Fan Longfei, Zheng Hui, Zhao Guangming, H. Shun-ji
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引用次数: 0

摘要

本文考虑了复杂的信号和系统模型,导出了一类基于高阶累积量的盲反褶积准则。指出盲反卷积可以通过增大或减小系统输出的归一化累积量来实现。这是一种新的盲反褶积统计匹配方法。作为实例,提出了一种新的盲反卷积(均衡)算法,并通过计算机仿真验证了该算法的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A class of new criteria for blind deconvolution
Complex signal and system models are considered in this paper, and a class of new criteria, which is based on the higher-order cumulant, is derived for blind deconvolution. It is pointed out that blind deconvolution may be realized by maximizing or minimizing the normalized cumulant of the system output. This is a new approach to statistical matching for blind deconvolution. As an example, a new blind deconvolution (equalization) algorithm is proposed, and computer simulation results are included to demonstrate the performance of the proposed algorithm.
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