DocumentCode
2331760
Title
Estimation of Mixtures of Symmetric Alpha Stable Distributions With an Unknown Number of Components
Author
Salas-González, D. ; Kuruoglu, E.E. ; Ruiz, D.P.
Author_Institution
Dept. of Appl. Phys., Granada Univ.
Volume
5
fYear
2006
fDate
14-19 May 2006
Abstract
In this work, we study the estimation of mixtures of symmetric alpha-stable distributions using Bayesian inference. We utilise numerical Bayesian sampling techniques such as Markov chain Monte Carlo (MCMC). Our estimation technique is capable of estimating also the number of alpha-stable components in the mixture in addition to the component parameters and mixing coefficients which is accomplished by using the reversible jump MCMC (RJMCMC) algorithm
Keywords
Markov processes; Monte Carlo methods; inference mechanisms; signal sampling; Bayesian inference; Markov chain Monte Carlo; numerical Bayesian sampling techniques; symmetric alpha stable distributions; Bayesian methods; Gaussian processes; Inference algorithms; Monte Carlo methods; Parameter estimation; Physics; Probability distribution; Random variables; Sampling methods; Signal processing algorithms;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on
Conference_Location
Toulouse
ISSN
1520-6149
Print_ISBN
1-4244-0469-X
Type
conf
DOI
10.1109/ICASSP.2006.1661333
Filename
1661333
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