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  • 标题:On kernel structures for regularized system identification (II): a system theory perspective *
  • 本地全文:下载
  • 作者:Tianshi Chen ; Lennart Ljung
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2015
  • 卷号:48
  • 期号:28
  • 页码:1041-1046
  • DOI:10.1016/j.ifacol.2015.12.268
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractIn this companion paper, we will continue our discussions on the issue of kernel structure design and we will focus on the system theory perspective. In particular, we will study the stability, maximum entropy property, Markov property and model complexity of the recently introduced state space model induced kernel. These findings motivate a system theory perspective to understand the behavior of kernels and to construct more general kernels.
  • 关键词:KeywordsSystem identificationmachine learningregularization methodskernel methods
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