Newton Polytopes of Two-Dimensional Hidden Markov Models

Introducing Busy Customer Portfolio Using Hidden Markov Model

Due to the effective role of Markov models in customer relationship management (CRM), there is a lack of comprehensive literature review which contains all related literatures. In this paper the focus is on academic databases to find all the articles that had been published in 2011 and earlier. One hundred articles were identified and reviewed to find direct relevance for applying Markov models...

Speaker Independent Speech Recognition Using Hidden Markov Models for Persian Isolated Words

Speaker Independent Speech Recognition Using Hidden Markov Models for Persian Isolated Words

Quasi-Newton method for maximum likelihood estimation of hidden Markov models

Hidden Markov models (HMMs) are used in many signal processing applications including speech recognition, blind equalization of digital communications channels, etc. The most widely used method for maximum likelihood estimation of HMM parameters is the forward-backward (or BaumWelch) algorithm which is an early example of application of the Expectation-Maximization (EM) principle. In this contr...

Bayesian inference by simulation in a stochastic model from hematology

A particular Markov chain Monte Carlo algorithmis constructed to allow Bayesian inference in a hidden Markov model used in hematology. The algorithm has an outer Gibbsian structure, and incorporates both Metropolis and Hastings updates to move through the space of possible hidden states. While somewhat sophisticated, this algorithm still has problems getting around the infinite-dimensional spac...