Selection of a time-varying Volterra model using multiple hypothesis testing

M. Green, A. Zoubir
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引用次数: 2

Abstract

We consider the system identification problem using a time-varying quadratic Volterra model. To enable identification a set of known basis sequences are used in the model to approximate the time-variation of the true system. To reduce the number of parameters in the model we wish to determine which individual sequences are significant in this approximation. Multiple hypothesis testing procedures are employed to select significant sequences. The tests include the Bonferroni test, Holm's (1979) sequentially rejective Bonferroni test, and Hommel's (1988) extension to Simes' (1986) procedure [5].
用多重假设检验选择时变Volterra模型
我们使用时变二次Volterra模型来考虑系统辨识问题。为了使识别成为可能,在模型中使用一组已知的基序列来近似真实系统的时变。为了减少模型中参数的数量,我们希望确定哪些单独的序列在这个近似中是显著的。采用多重假设检验程序选择显著序列。这些检验包括Bonferroni检验、Holm(1979)的顺序拒绝性Bonferroni检验和Hommel(1988)对Simes(1986)程序的扩展[5]。
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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