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文章基本信息

  • 标题:Identification of noisy input-output FIR models with colored output noise
  • 本地全文:下载
  • 作者:Matteo Barbieri ; Roberto Diversi
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2020
  • 卷号:53
  • 期号:2
  • 页码:901-906
  • DOI:10.1016/j.ifacol.2020.12.850
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThis paper deals with the identification of FIR models corrupted by white input noise and colored output noise. An identification algorithm that exploits the properties of both the dynamic Frisch scheme and the high-order Yule-Walker (HOYW) equations is proposed. It is shown how the HOYW equations allow to define a selection criterion for identifying the input noise variance (and then the FIR coefficients) within the Frisch locus of solutions. The proposed approach does not require any a priori knowledge about the input and output noise variances. The algorithm performance is assessed by means of Monte Carlo simulations.
  • 关键词:KeywordsSystem identificationFIR modelserrors-in-variables modelsFrisch schemehigh-order Yule-Walker equations
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