基于伪随机序列的增量维纳滤波反卷积算法

Zheng Xiaodan, Hao Kaixue, L. Mei
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引用次数: 3

摘要

将维纳滤波反褶积算法应用于受带外噪声变化影响,稳定性差、识别效果不佳的相关识别方法。从这一不良后果出发,分析了维纳滤波反卷积算法对噪声自适应不理想的原因。提出了用于相关识别方法的增量维纳滤波器,研究了增量维纳滤波器允许迭代估计的特点,进一步改进了维纳滤波反卷积算法。最后,实验表明,增量维纳滤波反褶积算法对噪声有较好的滤波效果,可以提高反褶积的精度,在相关识别方法的应用中获得较好的识别效果
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The deconvolution algorithm of incremental wiener filtering based on pseudo-random sequences
The Wiener filtering deconvolution algorithm applied to the correlation identification method which stability is poor and identification effect is undesirable that caused by the noise change of outside the band. The reasons of Wiener filtering deconvolution algorithm which adaptive of noise is unsatisfactory is analyzed by this undesirable consequence. The incremental wiener filter that used in correlation identification method is proposed: We study the characteristic of incremental wiener filter that solution is allowed for iterative estimation to improve Wiener filtering deconvolution algorithm further. Finally, the experiments indicate that the incremental wiener filtering deconvolution algorithm has better filtering effect to the noise that can improve the precision of deconvolution and obtain better recognition effect in the application of the correlation identification method
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