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Orthogonalization of correlated Gaussian signals for Volterra system identification

机译:相关高斯信号的正交化用于Volterra系统识别

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This article presents a simple method for orthogonalizing correlated Gaussian input signals for identification of truncated Volterra systems of arbitrary order of nonlinearity P and memory length N. The procedure requires a Gram-Schmidt orthogonalizer for a vector containing N elements and some nonlinear processing of the output elements of the Gram-Schmidt processor. However, the nonlinear processors do not depend on the statistics of the input signals and, consequently, are easy to design and implement.
机译:本文提供了一种简单的方法,用于对相关的高斯输入信号进行正交化,以识别具有任意非线性P和存储长度N的截断的Volterra系统。该过程需要Gram-Schmidt正交化器用于包含N个元素的向量以及输出的一些非线性处理Gram-Schmidt处理器的元素。但是,非线性处理器不依赖于输入信号的统计,因此易于设计和实现。

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