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Continuous-time DC kernel - a stable generalized first order spline kernel
Chinese University of Hong Kong, Peoples R China.
University of Padua, Italy.
University of Padua, Italy.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
2016 (English)In: 2016 IEEE 55TH CONFERENCE ON DECISION AND CONTROL (CDC), IEEE , 2016, 4647-4652 p.Conference paper, Published paper (Refereed)
Abstract [en]

The stable spline kernel and the diagonal correlated kernel are two kernels that have been tested extensively in kernel-based regularization methods for LTI system identification. As shown in our recent works, although these two kernels are introduced in different ways, they share some common features, e.g., they all belong to the class of exponentially convex locally stationary kernels, and state-space model induced kernels. In this work, we further show that similar to the derivation of the stable spline kernel, the continuous-time diagonal correlated kernel can be derived by applying the same "stable" coordinate change to a "generalized" first order spline kernel, and thus can be interpreted as a stable generalized first order spline kernel. This interpretation provides new facets to understand the properties of the diagonal correlated kernel. Due to this interpretation, new eigendecompositions, explicit expression of the norm, and new maximum entropy interpretation of the diagonal correlated kernel are derived accordingly.

Place, publisher, year, edition, pages
IEEE , 2016. 4647-4652 p.
Series
IEEE Conference on Decision and Control, ISSN 0743-1546
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-138329DOI: 10.1109/CDC.2016.7798977ISI: 000400048104135ISBN: 978-1-5090-1837-6 (print)OAI: oai:DiVA.org:liu-138329DiVA: diva2:1109025
Conference
55th IEEE Conference on Decision and Control (CDC)
Note

Funding Agencies|Chinese University of Hong Kong, Shenzhen; Thousand Youth Talents Plan - central government of China; Swedish Research Council [2014-5894]; ERC advanced grant LEARN - European Research Council [267381]; Linnaeus Center CADICS - Swedish Research Council; MIUR FIRB project "Learning meets time" [RBFR12M3AC]; European Communitys Seventh Framework Programme [FP7] [257462]

Available from: 2017-06-13 Created: 2017-06-13 Last updated: 2017-06-13

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CiteExportLink to record
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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
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  • asciidoc
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