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  • 标题:Efficient Implementation of Kernel Regularization based on ADMM
  • 本地全文:下载
  • 作者:Yusuke Fujimoto
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2021
  • 卷号:54
  • 期号:7
  • 页码:744-748
  • DOI:10.1016/j.ifacol.2021.08.450
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThis work discusses about an efficient implementation of the kernel regularization method. In particular, this work focuses on Alternating Direction Method of Multipliers (ADMM) which is one of the convex optimization methods. This work employs two assumptions; (1) the identification input is periodic, and (2) the kernel matrix is tridiagonal. It is shown that ADMM updates can be implemented efficiently under these assumptions. A numerical example is shown to demonstrate the effectiveness of the proposed method.
  • 关键词:KeywordsNon-parametric identificationregularizationconvex optimizationkernel regularizationimpulse response
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