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Analysis and identification of complex stochastic systems admitting a flocking structure
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
2014 (English)In: IFAC Proceedings Volumes (IFAC-PapersOnline), 2014, 2323-2328 p.Conference paper, Published paper (Refereed)
Abstract [en]

We discuss a new modeling paradigm for large dimensional aggregates of stochastic systems by Generalized Factor Analysis (GFA) models. These models describe the data as the sum of a flocking plus an uncorrelated idiosyncratic component. The flocking component describes a sort of collective orderly motion which admits a much simpler mathematical description than the whole ensemble while the idiosyncratic component describes weakly correlated noise. The extraction of the dynamic flocking component is discussed for time-stationary systems.

Place, publisher, year, edition, pages
2014. 2323-2328 p.
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:kth:diva-175137Scopus ID: 2-s2.0-84929774258ISBN: 9783902823625 (print)OAI: oai:DiVA.org:kth-175137DiVA: diva2:860341
Conference
19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014, 24 August 2014 through 29 August 2014
Note

QC 20151012

Available from: 2015-10-12 Created: 2015-10-09 Last updated: 2015-10-12Bibliographically approved

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CiteExportLink to record
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  • apa
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