Modeling chaotic systems with hidden Markov models

Cory Myers, Andrew Singer, Frances Shin, Eugene Church

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

Abstract

The problem of modeling chaotic nonlinear dynamical systems using hidden Markov models is considered. A hidden Markov model for a class of chaotic systems is developed from noise-free observations of the output of that system. A combination of vector quantization and the Baum-Welch algorithm is used for training. The importance of this combined iterative approach is demonstrated. The model is then used for signal separation and signal detection problems. The difference between maximum likelihood signal estimation and maximum a posteriori signal estimation using a hidden Markov model is illustrated for a nonlinear dynamical system.

Original languageEnglish (US)
Title of host publicationICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages565-568
Number of pages4
ISBN (Electronic)0780305329
DOIs
StatePublished - 1992
Externally publishedYes
Event1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1992 - San Francisco, United States
Duration: Mar 23 1992Mar 26 1992

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume4
ISSN (Print)1520-6149

Other

Other1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1992
Country/TerritoryUnited States
CitySan Francisco
Period3/23/923/26/92

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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