Gerencsér, László and Molnár-Sáska, Gábor (2007) Identification of hidden Markov models - uniform LLN-s. In: - Springer, Berlin, pp. 135-149. ISBN 978-3-540-73569-4

Text pca5d6f0dd330483d94e2eb211f38ec1bandpi11 - Published Version Restricted to Registered users only Download (39kB)

Abstract

We consider hidden Markov processes in discrete time with a finite state space X and a general observation or read-out space Y. The identification of the unknown dynamics is carried out by the conditional maximum-likelihood method. The normalized log-likelihood function is shown to satisfy a uniform law of large numbers over certain compact subsets of the parameter space. Two cases are covered: first, when the running value of the transition probability matrix, denoted by Q is positive, second, when Q is primitive, but the read-out densities are strictly positive.

Item Type:	Book Section
Uncontrolled Keywords:	hidden Markov models, maximum-likelihood estimation, predictive filters, gradient filters, L-mixing.
Subjects:	Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány
Depositing User:	Eszter Nagy
Date Deposited:	11 Dec 2012 15:29
Last Modified:	11 Dec 2012 15:29
URI:	https://eprints.sztaki.hu/id/eprint/5000

Update Item