Approximate realization of hidden Markov chains

被引:5
作者
Finesso, L [1 ]
Spreij, P [1 ]
机构
[1] CNR, LADSEB, Inst Syst Sci & Bioengn, I-35127 Padua, Italy
来源
PROCEEDINGS OF 2002 IEEE INFORMATION THEORY WORKSHOP | 2002年
关键词
D O I
10.1109/ITW.2002.1115424
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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 py(.) of Y the weak realization problem consists in finding a Markov chain X and a function f such that, at least. distributionally, Y similar to 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 non-negative (componentwise) matrices related to the processes. To construct the realization we apply recent results on the approximate factorization of nonnegative matrices.
引用
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页码:90 / 93
页数:4
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