Digitale Medien
Springer
Journal of optimization theory and applications
84 (1995), S. 415-431
ISSN:
1573-2878
Schlagwort(e):
Kalman filtering
;
Karhunen-Loève expansion
;
stability
;
observability
;
controllability
Quelle:
Springer Online Journal Archives 1860-2000
Thema:
Mathematik
Notizen:
Abstract Several state-space models for estimating a second-order stochastic process are proposed in this paper on the basis of the approximate Karhunen-Loève expansion. Properties of these models are studied and then the Kalman filtering method is applied. The accuracy of the models on the basis of two different situations, deterministic or random inputs, is studied by means of a simulation of a Brownian motion.
Materialart:
Digitale Medien
URL:
http://dx.doi.org/10.1007/BF02192123
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