Title :
Recursive algorithms for estimation of hidden Markov models and autoregressive models with Markov regime
Author :
Krishnamurthy, Vikram ; Yin, George Gang
Author_Institution :
Dept. of Electr. & Electron. Eng., Univ. of Melbourne, Vic., Australia
fDate :
2/1/2002 12:00:00 AM
Abstract :
This paper is concerned with recursive algorithms for the estimation of hidden Markov models (HMMs) and autoregressive (AR) models under the Markov regime. Convergence and rate of convergence results are derived. Acceleration of convergence by averaging of the iterates and the observations are treated. Finally, constant step-size tracking algorithms are presented and examined
Keywords :
autoregressive processes; convergence of numerical methods; hidden Markov models; iterative methods; maximum likelihood estimation; recursive estimation; tracking; AR models; HMMs; Markov regime; autoregressive models; convergence; hidden Markov models; iterates; recursive algorithms; tracking algorithms; Approximation algorithms; Convergence; Hidden Markov models; Maximum likelihood estimation; Parameter estimation; Recursive estimation; Signal processing; Signal processing algorithms; Speech recognition; Stochastic processes;
Journal_Title :
Information Theory, IEEE Transactions on
