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Minimal dimensional linear filters for discrete-time Markov processes with finite state space

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2 Author(s)
G. B. Di Masi ; Dipartimento di Matematica Pura e Applicata, Padova Univ., Italy ; P. I. Kitsul

We consider a filtering problem for a discrete-time Markov process with k states observed in white Gaussian noise. It is known that in this situation the best linear estimate is given by a k-dimensional Kalman filter, and in some cases the dimension of such a filter can be reduced. Here, using a backward semimartingale description of the process and results from stochastic realization theory, we provide an algorithm for the construction of the minimal dimensional linear filter

Published in:

IEEE Transactions on Automatic Control  (Volume:41 ,  Issue: 10 )