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A stochastic multi-armed bandit approach to nonparametric H-norm estimation
KTH, School of Electrical Engineering (EES), Automatic Control.ORCID iD: 0000-0002-6322-7857
KTH, School of Electrical Engineering (EES), Automatic Control.ORCID iD: 0000-0002-8524-0649
KTH, School of Electrical Engineering (EES), Automatic Control.
KTH, School of Electrical Engineering (EES), Automatic Control.ORCID iD: 0000-0003-0355-2663
2017 (English)In: 56th IEEE Conference on Decision and Control, Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 4632-4637Conference paper, Published paper (Refereed)
Abstract [en]

We study the problem of estimating the largest gain of an unknown linear and time-invariant filter, which is also known as the H norm of the system. By using ideas from the stochastic multi-armed bandit framework, we present a new algorithm that sequentially designs an input signal in order to estimate this quantity by means of input-output data. The algorithm is shown empirically to beat an asymptotically optimal method, known as Thompson Sampling, in the sense of its cumulative regret function. Finally, for a general class of algorithms, a lower bound on the performance of finding the H-infinity norm is derived.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017. p. 4632-4637
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-223861DOI: 10.1109/CDC.2017.8264343ISI: 000424696904075Scopus ID: 2-s2.0-85046136421ISBN: 978-1-5090-2873-3 (print)OAI: oai:DiVA.org:kth-223861DiVA, id: diva2:1187905
Conference
56th IEEE Conference on Decision and Control
Funder
Swedish Research Council, 2015-04393; 2016-06079
Note

QC 20180306

Available from: 2018-03-06 Created: 2018-03-06 Last updated: 2019-08-27Bibliographically approved

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Müller, Matias I.Valenzuela, Patricio EstebanProutiere, AlexandreRojas, Cristian R.

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
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  • de-DE
  • en-GB
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Output format
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