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  • 标题:Tensor Factorization based Estimates of Parallel Wiener Hammerstein Models
  • 本地全文:下载
  • 作者:David T. Westwick ; Mariya Ishteva ; Philippe Dreesen
  • 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
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