4Approximate realization of hidden Markov chains

In this paper we consider the approximate realization problem for finite valued hidden Markov models i.e. stochastic processes Y=f(X) where X is a finite state Markov chain and f a many-to-one function. Given the laws p/sub Y/(/spl middot/) of Y the weak realization problem consists in finding a Mar...

Full description

Saved in:
Bibliographic Details
Published inProceedings of the IEEE Information Theory Workshop pp. 90 - 93
Main Authors Finesso, L., Spreij, P.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2002
Subjects
Biomedical engineering
Convergence
Hidden Markov models
Mathematics
Maximum likelihood estimation
Stochastic processes
Stochastic systems
Yttrium
Online AccessGet full text

Cover

More Information
Summary:In this paper we consider the approximate realization problem for finite valued hidden Markov models i.e. stochastic processes Y=f(X) where X is a finite state Markov chain and f a many-to-one function. Given the laws p/sub Y/(/spl middot/) of Y the weak realization problem consists in finding a Markov chain X and a function f such that, at least distributionally, Y/spl sim/f(X). The approximate realization problem consists in finding X and f such that Y and f (X) are close. The approximation criterion we use is the informational divergence between properly defined. nonnegative (componentwise) matrices related to the processes. To construct the realization we apply recent results on the approximate factorization of nonnegative matrices.
ISBN:9780780376298
0780376293
DOI:10.1109/ITW.2002.1115424