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
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;
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
DOI :
10.1109/SSAP.2000.870097
