DocumentCode :
919777
Title :
On the approximation of optimal realizable linear filters using a Karhunen-Loeve expansion (Corresp.)
Author :
Fortmann, T.E. ; Anderson, B.D.O.
Volume :
19
Issue :
4
fYear :
1973
fDate :
7/1/1973 12:00:00 AM
Firstpage :
561
Lastpage :
564
Abstract :
The Karhunen-Loève expansion of a random process is used to derive the impulse response of the optimal realizable linear estimator for the process. The expansion is truncated to yield an approximate state-variable model of the process in terms of the first 
eigenvalues and eigenfunctions. The Kalman-Bucy filter for this model provides an approximate realizable linear estimator which approaches the optimal one as 
. A bound on the truncation error is obtained.
eigenvalues and eigenfunctions. The Kalman-Bucy filter for this model provides an approximate realizable linear estimator which approaches the optimal one as . A bound on the truncation error is obtained.Keywords :
Estimation; Karhunen-Loeve series; Eigenvalues and eigenfunctions; Gaussian noise; Hilbert space; Nonlinear filters; Random processes; Shape; Space technology; Time series analysis;
fLanguage :
English
Journal_Title :
Information Theory, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9448
Type :
jour
DOI :
10.1109/TIT.1973.1055039
Filename :
1055039
Link To Document :
