Adaptive estimation of HMM transition probabilities


Autoria(s): Ford, Jason J.; Moore, John B.
Data(s)

01/05/1998

Resumo

This paper presents new schemes for recursive estimation of the state transition probabilities for hidden Markov models (HMM's) via extended least squares (ELS) and recursive state prediction error (RSPE) methods. Local convergence analysis for the proposed RSPE algorithm is shown using the ordinary differential equation (ODE) approach developed for the more familiar recursive output prediction error (RPE) methods. The presented scheme converges and is relatively well conditioned compared with the ...

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/78147/

Publicador

IEEE

Relação

http://eprints.qut.edu.au/78147/1/162.PDF

DOI:10.1109/78.668799

Ford, Jason J. & Moore, John B. (1998) Adaptive estimation of HMM transition probabilities. IEEE Transactions on Signal Processing, 46(5), pp. 1374-1385.

Direitos

Copyright 1998 IEEE

Fonte

School of Electrical Engineering & Computer Science; Science & Engineering Faculty

Palavras-Chave #090602 Control Systems Robotics and Automation
Tipo

Journal Article