DocumentCode
2025030
Title
A Monte Carlo Algorithm for Optimal Quantization in Hidden Markov Models
Author
Tadic, V.B. ; Doucet, A.
Author_Institution
Univ. of Bristol, Bristol
fYear
2007
fDate
24-29 June 2007
Firstpage
1121
Lastpage
1125
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.
Keywords
Monte Carlo methods; gradient methods; hidden Markov models; quantisation (signal); signal sampling; stochastic processes; Monte Carlo algorithm; Monte Carlo sampling; gradient estimation techniques; hidden Markov models; optimal quantization; stochastic approximation; Algorithm design and analysis; Analytical models; Approximation algorithms; Hidden Markov models; Monte Carlo methods; Quantization; Signal generators; Statistics; Stochastic processes; Zinc;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory, 2007. ISIT 2007. IEEE International Symposium on
Conference_Location
Nice
Print_ISBN
978-1-4244-1397-3
Type
conf
DOI
10.1109/ISIT.2007.4557374
Filename
4557374
Link To Document