DocumentCode
2433934
Title
Stochastic algorithms for marginal MAP retrieval of sinusoids in non-Gaussian noise
Author
Andrieu, Christophe ; Doucet, Arnaud
Author_Institution
Dept. of Eng., Cambridge Univ., UK
fYear
2000
fDate
2000
Firstpage
131
Lastpage
135
Abstract
In this paper we propose a method to estimate the frequencies of sinusoids embedded in non-Gaussian noise. We model the noise using mixtures of Gaussians and propose two original, efficient algorithms that allow for the marginal maximum a posteriori (MAP) estimation of the sinusoid parameters to be estimated. Outline of the proof of convergence of the algorithms is also given and simulation results are presented
Keywords
convergence of numerical methods; frequency estimation; maximum likelihood estimation; random noise; signal processing; spectral analysis; stochastic processes; frequency estimation; marginal MAP sinusoid retrieval; marginal maximum a posteriori estimation; non-Gaussian noise; signal processing; sinusoid parameters; spectral estimation; stochastic algorithms; Algorithm design and analysis; Bayesian methods; Frequency estimation; Gaussian distribution; Gaussian noise; Monte Carlo methods; Noise level; Parameter estimation; Signal processing algorithms; Stochastic resonance;
fLanguage
English
Publisher
ieee
Conference_Titel
Statistical Signal and Array Processing, 2000. Proceedings of the Tenth IEEE Workshop on
Conference_Location
Pocono Manor, PA
Print_ISBN
0-7803-5988-7
Type
conf
DOI
10.1109/SSAP.2000.870097
Filename
870097
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