DocumentCode
801955
Title
System identification using partitioned least squares
Author
Karny, M. ; Warwick, K.
Author_Institution
Inst. of Inf. Theory & Autom., Czech Acad. of Sci., Prague, Czech Republic
Volume
142
Issue
3
fYear
1995
fDate
5/1/1995 12:00:00 AM
Firstpage
223
Lastpage
228
Abstract
A novel partitioned least squares (PLS) algorithm is presented, in which estimates from several simple system models are combined by means of a Bayesian methodology of pooling partial knowledge. The method has the added advantage that, when the simple models are of a similar structure, it lends itself directly to parallel processing procedures, thereby speeding up the entire parameter estimation process by several factors
Keywords
Bayes methods; autoregressive processes; least squares approximations; parameter estimation; Bayesian method; parallel processing; parameter estimation; partitioned least squares; system identification; system models;
fLanguage
English
Journal_Title
Control Theory and Applications, IEE Proceedings -
Publisher
iet
ISSN
1350-2379
Type
jour
DOI
10.1049/ip-cta:19951877
Filename
392496
Link To Document