Journal article

A Monte Carlo algorithm for optimal quantization in hidden Markov models

Abstract:: In this paper, the problem of the optimal quantization of a signal generated by a hidden Markov model is considered. For this problem, an efficient algorithm based on Monte Carlo sampling, gradient estimation techniques and stochastic approximation is proposed. The properties of the proposed algorithm are analyzed both theoretically and through simulations. ©2007 IEEE.

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APA Style

Tadić, V., & Doucet, A. (2007). A Monte Carlo algorithm for optimal quantization in hidden Markov models. IEEE International Symposium on Information Theory - Proceedings, 1121–1125.

MLA Style

Tadić, V., and A. Doucet. “A Monte Carlo Algorithm for Optimal Quantization in Hidden Markov Models.” IEEE International Symposium on Information Theory - Proceedings, 2007, pp. 1121–25.

Chicago Style

Tadić, V, and A Doucet. 2007. “A Monte Carlo Algorithm for Optimal Quantization in Hidden Markov Models.” IEEE International Symposium on Information Theory - Proceedings, 1121–25.
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Publisher copy:: 10.1109/ISIT.2007.4557374

Authors

+ Tadić, V More by this author

Role:: Author

+ Doucet, A More by this author

Role:: Author

Journal:: IEEE International Symposium on Information Theory - Proceedings More from this journal
Pages:: 1121-1125
Publication date:: 2007-01-01
DOI:: 10.1109/ISIT.2007.4557374

Pubs id:: pubs:172747
UUID:: uuid:547a6d3d-363c-4038-8ab4-47b2d144bf52
Local pid:: pubs:172747
Source identifiers:: 172747
Deposit date:: 2012-12-19

Terms of use

Copyright date:: 2007

Licence:: Terms and Conditions of Use for Oxford University Research Archive

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