Title :
Adaptive estimation for a linear system with interrupted observation
Author :
Sawaragi, Y. ; Katayama, T. ; Fujishige, S.
Author_Institution :
Kyoto University, Kyoto, Japan
fDate :
4/1/1973 12:00:00 AM
Abstract :
This short paper is concerned with the Bayesian estimation problem for a linear system with the interrupted observation mechanism that is expressed in terms of the stationary two-state Markov chain with unknown transition probabilities. Derived is the approximate minimum variance adaptive estimator algorithm coupled with the estimation of the unknown transition probabilities.
Keywords :
Adaptive estimation; Bayes procedures; Linear systems, time-varying discrete-time; Sequential estimation; State estimation; Adaptive algorithm; Adaptive estimation; Bayesian methods; Control theory; Covariance matrix; Difference equations; Kalman filters; Linear systems; State estimation; Vectors;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.1973.1100251
