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SUMMARY:Behavioral approach to system identification and data-driven signa
 l processing
DTSTART:20230310T110000
DTEND:20230310T120000
DTSTAMP:20260407T061609Z
UID:82cbc96f6a9a8eb7e0a6151ca25edda447fd3e4604904d9de89b1f44
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Ivan Markovsky\, International Centre for Numerical Meth
 ods in Engineering\, Barcelona\n\n \nAbstract: The talk gives a self-cont
 ained derivation of data-driven methods developed in the behavioral settin
 g and demonstrates their relevance for applications. The methods reviewed 
 combine ideas from subspace identification and machine learning. A key ide
 a from subspace identification is that under a persistency of excitation c
 ondition\, the image of a Hankel matrix constructed from the data is equal
  to the behavior of the system. This result allows construction of traject
 ories directly from data\, which in turn allows solving data-driven simula
 tion\, smoothing\, and control problems. The construction requires solutio
 n of a system of linear equations only. It assumes\, however\, that the da
 ta is obtained from a linear time-invariant system. For noisy data and non
 linear systems\, sparsity promoting regularization is an effective heurist
 ic. As a show case of the data-driven representation\, a direct data-drive
 n method for frequency response estimation is shown.\n\nBio: Ivan Markovsk
 y is an ICREA professor at the International Centre for Numerical Methods 
 in Engineering\, Barcelona. He received his Ph.D.\ndegree in Electrical En
 gineering from the Katholieke Universiteit Leuven in February 2005. From 2
 006 to 2012 he was an Assistant Professor at the School of Electronics and
  Computer Science of the University of Southampton and from 2012 to 2022 a
 n Associate Professor at the Vrije Universiteit Brussel. He is a recipient
  of an ERC starting grant "Structured low-rank approximation: Theory\, alg
 orithms\, and applications" 2010--2015\, Householder Prize honorable menti
 on 2008\, and research mandate by the Vrije Universiteit Brussel research 
 council 2012--2022. His main research interests are computational methods 
 for system theory\, identification\, and data-driven control in the behavi
 oral setting
LOCATION:ME C2 405 https://plan.epfl.ch/?room==ME%20C2%20405
STATUS:CONFIRMED
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