NDLI: On the relation between CCA and predictor-based subspace identification.

Content Provider	IEEE Xplore Digital Library
Author	Chiuso, A.
Copyright Year	2005
Description	Author affiliation: Dipartimento di Ingegneria dell’Informazione, Università di Padova Via Gradenigo 6/A, 35131 Padova, Italy chiuso@dei.unipd.it (Chiuso, A.)
Abstract	There is experimental evidence that a recently proposed subspace algorithm based on predictor identification has a behavior which is very close to prediction error methods in certain simple examples; this observation raises a question concerning its optimality. It is known that time series identification using the Canonical Correlation Analysis (CCA) approach is asymptotically efficient. Asymptotic optimality of CCA has also been proved when measured inputs are white. In this paper we study the relation between the standard CCA approach and the recently proposed subspace procedure based on predictor identification $(PBSID^{1}from$ now on). In this paper we work under the assumption that there is no feedback; it is shown that CCA and PBSID are asymptotically equivalent precisely in the situations when CCA is optimal. The equivalence holds only asymptotically in the number of data and in the limit as the past horizon goes to infinity. Using some recent results on the asymptotic variance we report counter-examples showing that PBSID is not efficiency in general when measured inputs are not white.
Starting Page	4976
Ending Page	4982
File Size	205658
Page Count	7
File Format	PDF
ISBN	0780395670
DOI	10.1109/CDC.2005.1582950
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-12-15
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	IEEE/EUCA
Subject Keyword	Algorithm design and analysis Prediction algorithms Time series analysis H infinity control Performance analysis Terminology Time measurement State-space methods State feedback
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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