Bayesian Estimation of Sinusoidal Signals via Parallel Tempering
8th WSEAS Int Conference on Signal Processing/3rd WSEAS Int Symposium on Wavelets Theory and Applicat in Appl Math, Signal Proc and Modern Sci, İstanbul, Turkey, 30 May - 01 June 2009, pp.67-72, (Full Text)
- Publication Type: Conference Paper / Full Text
- Volume:
- City: İstanbul
- Country: Turkey
- Page Numbers: pp.67-72
- Istanbul University Affiliated: No
Abstract
This paper deals with a parameter estimation problem within a Bayesian framework. Performing Bayesian inference about the parameters is a challenging computational problem and requires an evaluation of complicated high-dimensional integrals. In this context, we make an attempt to improve an efficient stochastic procedure, proposed by Gregory, which is based on a parallel tempering Markov Chain Monte Carlo method (MCMC). We code its algorithm in Mathematica and then test it for estimating parameters of sinusoids corrupted by a random noise. Computer simulations support its effectiveness.