Title :
Filter stability for stochastic evolution equations
Author_Institution :
Imperial College, London, England
Abstract :
We describe how the Kalman filter associated with signal and observation processes defined through stochastic evolution equations is stable under the very weak hypotheses of stabilizability, detectability. The results find application in the filtering of signals governed by linear stochastic differential equations with delays; here the hypotheses are directly verifiable.
Keywords :
Differential equations; Kalman filters; Riccati equations; Signal processing; Stability; Stochastic processes;
Conference_Titel :
Decision and Control including the 15th Symposium on Adaptive Processes, 1976 IEEE Conference on
Conference_Location :
Clearwater, FL, USA
DOI :
10.1109/CDC.1976.267650
