Title :
Estimating rate constants in hidden Markov models by the EM algorithm
Author :
Michalek, Steffen ; Timmer, Jens
Author_Institution :
Center for Data Anal. & Modeling, Freiburg Univ., Germany
fDate :
1/1/1999 12:00:00 AM
Abstract :
The EM algorithm, e.g., the Baum-Welch (1970) re-estimation, is an important tool for parameter estimation in discrete-time hidden Markov models. We present a direct re-estimation of rate constants for applications in which the underlying Markov process is continuous in time. Previous estimation of discrete-time transition probabilities is not necessary
Keywords :
discrete time systems; hidden Markov models; maximum likelihood estimation; signal sampling; Baum-Welch re-estimation; EM algorithm; HMM; continuous time Markov process; discrete sampling; discrete-time hidden Markov models; discrete-time transition probabilities; maximum likelihood estimates; parameter estimation; rate constants estimation; Biomedical signal processing; Discrete wavelet transforms; Hidden Markov models; Maximum likelihood estimation; Notice of Violation; Parameter estimation; Signal processing algorithms; Speech analysis; Time series analysis; Wavelet packets;
Journal_Title :
Signal Processing, IEEE Transactions on
