New insights in the analysis of polynomial adaptive filters

Charles W. Therrien, W. K. Jenkins
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引用次数: 8

Abstract

New results are reported on the structure of the correlation matrix for the data vector in Volterra second order adaptive filters for a general colored Gaussian input process. The structure becomes apparent when the input to the quadratic part of the filter is represented as a Kronecker product of the vector of terms to the linear part, and the redundant terms in the product are not removed. This approach leads to bounds on the eigenvalues of the correlation matrix which characterize the performance of LMS algorithms, and suggestions for possibly improved nonlinear adaptive filtering algorithms.
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多项式自适应滤波器分析的新见解
本文报道了用于一般有色高斯输入过程的Volterra二阶自适应滤波器中数据向量相关矩阵结构的新结果。当滤波器的二次部分的输入被表示为线性部分的项向量的Kronecker积时,该结构变得明显,并且乘积中的冗余项没有被删除。该方法给出了表征LMS算法性能的相关矩阵特征值的边界,并对可能改进的非线性自适应滤波算法提出了建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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