Modeling chaotic systems with hidden Markov models

Cory Myers; Andrew Singer; Frances Shin; Eugene Church

doi:10.1109/ICASSP.1992.226385

Modeling chaotic systems with hidden Markov models

Cory Myers
, Andrew Singer
, Frances Shin
, Eugene Church

Office of the Dean of the College of Engineering and Applied Sciences

BAE Systems
Fire Support Armaments Center

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

19 Scopus citations

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 language	English
Title of host publication	ICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	565-568
Number of pages	4
ISBN (Electronic)	0780305329
DOIs	https://doi.org/10.1109/ICASSP.1992.226385
State	Published - 1992
Event	1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1992 - San Francisco, United States Duration: Mar 23 1992 → Mar 26 1992

Publication series

Name	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	4
ISSN (Print)	1520-6149

Conference

Conference	1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1992
Country/Territory	United States
City	San Francisco
Period	03/23/92 → 03/26/92

Access to Document

10.1109/ICASSP.1992.226385

Cite this

Myers, C., Singer, A., Shin, F., & Church, E. (1992). Modeling chaotic systems with hidden Markov models. In ICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing (pp. 565-568). Article 226385 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 4). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.1992.226385

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title = "Modeling chaotic systems with hidden Markov models",

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.",

author = "Cory Myers and Andrew Singer and Frances Shin and Eugene Church",

note = "Publisher Copyright: {\textcopyright} 1992 IEEE.; 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1992 ; Conference date: 23-03-1992 Through 26-03-1992",

year = "1992",

doi = "10.1109/ICASSP.1992.226385",

language = "English",

series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "565--568",

booktitle = "ICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing",

}

Myers, C, Singer, A, Shin, F & Church, E 1992, Modeling chaotic systems with hidden Markov models. in ICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing., 226385, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, vol. 4, Institute of Electrical and Electronics Engineers Inc., pp. 565-568, 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1992, San Francisco, United States, 03/23/92. https://doi.org/10.1109/ICASSP.1992.226385

Modeling chaotic systems with hidden Markov models. / Myers, Cory; Singer, Andrew; Shin, Frances et al.
ICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing. Institute of Electrical and Electronics Engineers Inc., 1992. p. 565-568 226385 (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 4).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Modeling chaotic systems with hidden Markov models

AU - Myers, Cory

AU - Singer, Andrew

AU - Shin, Frances

AU - Church, Eugene

PY - 1992

Y1 - 1992

N2 - 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.

AB - 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.

UR - https://www.scopus.com/pages/publications/80051947327

U2 - 10.1109/ICASSP.1992.226385

DO - 10.1109/ICASSP.1992.226385

M3 - Conference contribution

AN - SCOPUS:80051947327

T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

SP - 565

EP - 568

BT - ICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1992

Y2 - 23 March 1992 through 26 March 1992

ER -

Myers C, Singer A, Shin F, Church E. Modeling chaotic systems with hidden Markov models. In ICASSP 1992 - 1992 International Conference on Acoustics, Speech, and Signal Processing. Institute of Electrical and Electronics Engineers Inc. 1992. p. 565-568. 226385. (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). doi: 10.1109/ICASSP.1992.226385

Modeling chaotic systems with hidden Markov models

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