文章基本信息

标题：Tensor Factorization based Estimates of Parallel Wiener Hammerstein Models
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作者：David T. Westwick ; Mariya Ishteva ; Philippe Dreesen 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2017
卷号：50
期号：1
页码：9468-9473
DOI：10.1016/j.ifacol.2017.08.1470
语种：English
出版社：Elsevier
摘要：AbstractFactoring the third-order Volterra kernel of a Wiener-Hammerstein model to recover the impulse responses of its two constituent linear systems is a common example in the multilinear algebra literature. Since recent progress in regularization-based system identification has enabled the practical estimation of the third-order Volterra kernel, these tensor factorization based approaches have become attractive. We extend one of these Wiener-Hammerstein factorization methods to the case of the Parallel Wiener-Hammerstein model, since, unlike the WH model, this structure is a universal approximator for Volterra systems. The efficacy of the method is demonstrated using numerical simulations.
关键词：KeywordsBlock Structured ModelsVolterra KernelsTensorsCPD