Title :
Adjoint processes for Markov chains observed in Gaussian noise
Author :
Aggoun, L. ; Elliott, R.J. ; Moore, J.B.
Author_Institution :
Dept. of Stat. & Appl. Probability, Alberta Univ., Edmonton, Alta., Canada
Abstract :
A discrete time partially observed control problem is considered in which the dynamics of the system are described by a finite state Markov chain observed in Gaussian noise. A change of measure is introduced under which the observations are independent random variables. The unnormalized conditional probabilities of the Markov chain can be taken as information states and the problem discussed in separated form. An adjoint process is defined, and a minimum principle is obtained
Keywords :
Markov processes; discrete time systems; probability; state estimation; Gaussian noise; adjoint process; discrete time partially observed control problem; dynamics; finite state Markov chain; independent random variables; minimum principle; unnormalized conditional probabilities; Costs; Density measurement; Filtration; Gaussian noise; Optimal control; Probability; Random variables; Statistics; Time measurement; Yttrium;
Conference_Titel :
Signals, Systems and Computers, 1992. 1992 Conference Record of The Twenty-Sixth Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
0-8186-3160-0
DOI :
10.1109/ACSSC.1992.269242
