Bayesian Estimation of Sinusoidal Signals via Parallel Tempering - (:unkn) unknown (WORLD SCIENTIFIC AND ENGINEERING ACAD AND SOC, 2009)
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.
Keywords: Bayeslan Estimation; Harmonic Sinusoldal Signals; Parallel Tempering; Markov Chain Monte Carlo; PARAMETER-ESTIMATION