Analysis and identification of complex stochastic systems admitting a flocking structure
2014 (English)In: IFAC Proceedings Volumes (IFAC-PapersOnline), 2014, 2323-2328 p.Conference paper (Refereed)
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.
IdentifiersURN: urn:nbn:se:kth:diva-175137ScopusID: 2-s2.0-84929774258ISBN: 9783902823625OAI: oai:DiVA.org:kth-175137DiVA: diva2:860341
19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014, 24 August 2014 through 29 August 2014
QC 201510122015-10-122015-10-092015-10-12Bibliographically approved