Recovering sinusoids from noisy data using bayesian inference with simulated annealing

ÜSTÜNDAĞ D., Cevri M.

Mathematical and Computational Applications, vol.16, no.2, pp.382-391, 2011 (Scopus) identifier

  • Publication Type: Article / Article
  • Volume: 16 Issue: 2
  • Publication Date: 2011
  • Doi Number: 10.3390/mca16020382
  • Journal Name: Mathematical and Computational Applications
  • Journal Indexes: Scopus, TR DİZİN (ULAKBİM)
  • Page Numbers: pp.382-391
  • Keywords: Bayesian Statistical Inference Simulated Annealing, Cramér-Rao lower bound, Parameter estimations, Power Spectral Density
  • Istanbul University Affiliated: No

Abstract

In this paper, we studied Bayesian analysis proposed by Bretthorst[6] for a general signal model equation and combined it with a simulated annealing (SA) algorithm to obtain a global maximum of a posterior probability density function (PDF) for frequencies. Thus, this analysis offers different approach to finding parameter values through a directed, but random, search of the parameter space. For this purpose, we developed a Mathematica code of this Bayesian approach together with SA and used it for recovering sinusoids from noisy data. Simulations results support its effectiveness. Copyright © Association for Scientific Research.