DocumentCode
2108071
Title
Joint Bayesian detection and estimation of sinusoids embedded in noise
Author
Andrieu, Christophe ; Doucet, Arnaud ; Duvant, P.
Author_Institution
CNRS, Cergy, France
Volume
4
fYear
1998
fDate
12-15 May 1998
Firstpage
2245
Abstract
In this paper we address the problem of the joint detection and estimation of sinusoids embedded in noise, from a Bayesian point of view. We first propose an original Bayesian model. A large number of parameters has to be estimated, including the number of sinusoids. No analytical developments can be performed. This leads us to design a new stochastic algorithm relying on reversible jump MCMC (Markov chain Monte Carlo). We obtain very satisfactory results
Keywords
Bayes methods; Markov processes; Monte Carlo methods; noise; parameter estimation; signal detection; Markov chain Monte Carlo; joint Bayesian detection estimation; reversible jump MCMC; sinusoids; stochastic algorithm; Algorithm design and analysis; Bayesian methods; Gaussian noise; Integrated circuit modeling; Integrated circuit noise; Performance analysis; Probability distribution; Signal processing algorithms; Stochastic processes; Stochastic resonance;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
Conference_Location
Seattle, WA
ISSN
1520-6149
Print_ISBN
0-7803-4428-6
Type
conf
DOI
10.1109/ICASSP.1998.681595
Filename
681595
Link To Document