A new maximum likelihood gradient algorithm for on-line hidden Markov model identification

Lain B. Collings, Tobias Ryden

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

15 Citations (Scopus)

Abstract

This paper presents a new algorithm for on-line identification of hidden Markov model (HMM) parameters. The scheme is gradient based, and provides parameter estimates which recursively maximise the likelihood function. It is therefore a recursive maximum likelihood (RML) algorithm, and it has optimal asymptotic properties. The only current on-line HMM identification algorithm with anything other than suboptimal rate of convergence is based on a prediction error (PE) cost function. As well as presenting a new algorithm, this paper also highlights and explains a counter-intuitive convergence problem for the current recursive PE (RPE) algorithm, when operating in low noise conditions. Importantly, this problem does not exist for the new RML algorithm. Simulation studies demonstrate the superior performance of the new algorithm. compared to current techniques.

Original languageEnglish
Title of host publicationProceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 1998
Place of PublicationPiscataway, N.J.
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages2261-2264
Number of pages4
Volume6
ISBN (Electronic)0780344308, 0780344316
ISBN (Print)0780344286, 0780344294
DOIs
Publication statusPublished - May 1998
Externally publishedYes
Event1998 23rd IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP - 1998 - Seattle, United States
Duration: 12 May 199815 May 1998

Other

Other1998 23rd IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP - 1998
CountryUnited States
CitySeattle
Period12/05/9815/05/98

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    Collings, L. B., & Ryden, T. (1998). A new maximum likelihood gradient algorithm for on-line hidden Markov model identification. In Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 1998 (Vol. 6, pp. 2261-2264). [681599] Piscataway, N.J.: Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICASSP.1998.681599