DocumentCode :
850469
Title :
Deterministic balancing and stochastic model reduction
Author :
Vaccaro, Richard J.
Author_Institution :
University of Rhode Island, Kingston, RI, USA
Volume :
30
Issue :
9
fYear :
1985
fDate :
9/1/1985 12:00:00 AM
Firstpage :
921
Lastpage :
923
Abstract :
A recent approach to the deterministic model reduction problem is based on the notion of balancing. However, the original development of deterministic balancing did not contain any statistical considerations with which to develop a stochastic model reduction algorithm. Nevertheless, it is shown in this note that there are two stochastic model reduction algorithms in the literature which result in a deterministically balanced model. Their equivalence with deterministic balancing provides a stochastic interpretation to the deterministic algorithm.
Keywords :
Linear systems, stochastic; Reduced-order systems, linear; Stochastic systems, linear; Automatic control; Controllability; Equations; Independent component analysis; Linear systems; Observability; Reduced order systems; Singular value decomposition; Stochastic processes; Technological innovation;
fLanguage :
English
Journal_Title :
Automatic Control, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9286
Type :
jour
DOI :
10.1109/TAC.1985.1104087
Filename :
1104087
Link To Document :
بازگشت