DocumentCode
2601095
Title
Bayesian estimation of the variance of a jitter using MCMC
Author
Andrieu, Christophe ; Doucet, Arnaud ; Duvant, P.
Author_Institution
Groupe Signal, ENSEA-ETIS, Cergy Pontoise, France
fYear
1996
fDate
24-26 Jun 1996
Firstpage
24
Lastpage
27
Abstract
The problem treated in this paper is the Bayesian estimation of the variance of the sampling jitter occurring when a process is irregularly observed. This problem is often met in practice, and has already being examined using higher order statistics. The Bayesian solution to this problem is performed using powerful stochastic algorithms, the MCMC (Markov chain Monte Carlo) methods
Keywords
Bayes methods; Markov processes; Monte Carlo methods; jitter; parameter estimation; signal sampling; stochastic processes; Bayesian estimation; MCMC; Markov chain Monte Carlo methods; higher order statistics; sampling jitter variance; simulation; stochastic algorithms; Bayesian methods; Gaussian processes; Higher order statistics; Image processing; Jitter; Probability; Sampling methods; Signal processing; Signal processing algorithms; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Statistical Signal and Array Processing, 1996. Proceedings., 8th IEEE Signal Processing Workshop on (Cat. No.96TB10004
Conference_Location
Corfu
Print_ISBN
0-8186-7576-4
Type
conf
DOI
10.1109/SSAP.1996.534811
Filename
534811
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