Model Structure Selection - An Update
2014 (English)In: 2014 European Control Conference (ECC), IEEE , 2014, 2382-2385 p.Conference paper (Refereed)
While the topic has a long history in research, model structure selection is still one of the more challenging problems in system identification. In this tutorial we focus on impulse response modelling, and link classical techniques such as hypothesis testing and information criteria (e.g. AIC) to recent model estimation approaches, including regularisation. We discuss the problem from minimum mean-square error and maximum-likelihood perspectives.
Place, publisher, year, edition, pages
IEEE , 2014. 2382-2385 p.
Impulse response, Impulse testing, Maximum likelihood, Classical techniques, Hypothesis testing, Information criterion, Minimum mean-square error, Model estimation, Model structure selection, Regularisation
IdentifiersURN: urn:nbn:se:kth:diva-163502DOI: 10.1109/ECC.2014.6862639ISI: 000349955702114ScopusID: 2-s2.0-84911465723ISBN: 978-3-9524269-1-3OAI: oai:DiVA.org:kth-163502DiVA: diva2:801078
13th European Control Conference, ECC 2014, Strasbourg Convention and Exhibition Center Place de Bordeaux Strasbourg, France, 24 June 2014 through 27 June 2014
QC 201504082015-04-082015-04-072015-04-08Bibliographically approved