The performance of Hidden Markov Models (HMMs) targeted for complex real-world
applications are often degraded because they are designed a priori using limited training …

We consider a hidden Markov model with multidimensional observations, and with
misspecification, ie, the assumed coefficients (transition probability matrix and observation …

In this paper, we consider the consistency and asymptotic normality of the maximum
likelihood estimator for a possibly non-stationary hidden Markov model where the hidden …

We consider a hidden Markov model (HMM) with multidimensional observations, and where
the coefficients (transition probability matrix, and observation conditional densities) depend …

This paper is concerned with recursive algorithms for the estimation of hidden Markov
models (HMMs) and autoregressive (AR) models under the Markov regime. Convergence …

We consider partially observable Markov decision processes with finite or countably infinite
(core) state and observation spaces and finite action set. Following a standard approach, an …

Mathematics of Control, Signals, and Systems Page 1 Basic Properties of the Projective Product
with Application to Products of Column-Allowable Nonnegative Matrices* FrancËois Le Glandy …

This paper considers the state estimation of hidden Markov models by sensor networks. The
objective is to minimize the long term average of the mean square estimation error for the …

The authors investigate common properties of 3 types of filters obtained by considering
various stochastic models; Wiener filters, Kalman filters and hidden Markov model (HMM) …

We address the problem of filtering and fixed-lag smoothing for discrete-time and discrete-
state hidden Markov models (HMMs), with the intention of extending some important results …