Estimating parameters of sinusoids from noisy data using bayesian inference with simulated annealing - (:unkn) unknown (My University, 2008)
In this paper, we consider Bayesian analysis proposed by Bretthorst for estimating parameters of the corrupted signals and incorporate it with a simulated annealing algorithm to obtain a global maximum of the posterior probability density of the parameters. Thus, this analysis offers different approach to find parameter values through a directed, but random, search of the parameter space. For this purpose, we developed a Mathematica code of this Bayesian approach and used it for recovering sinusoids corrupted by random noise. The simulation results support the effectiveness of the method.
Keywords: Bayesian statistical inference; Optimization; Parameter estimations; Signal processing; Simulated annealing; Spectral analysis