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Transactions: WSEAS TRANSACTIONS ON SIGNAL PROCESSING
Transactions ID Number: 32-595
Full Name: Mehmet Cevri
Position: Ph.D. Candidate
Age: ON
Sex: Male
Address: The Department of Mathematics, Marmara University, Istanbul
Country: TURKEY
Tel: 0216 346 45 53
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E-mail address: mcevri@gmail.com
Other E-mails: dustundag@marmara.edu.tr
Title of the Paper: Bayesian Recovery of Sinüsoids from Noisy Data with Parallel Tempering
Authors as they appear in the Paper: M. Cevri & D. Üstündag
Email addresses of all the authors: mcevri@gmail.com
Number of paper pages: 10
Abstract: This paper deals with parameter estimation of sinusoids within a Bayesian framework. Bayesian inference about the parameters is a challenging computational problem and requires an evaluation of complicated high-dimensional integrals and a solution of multi dimensional optimization of posterior probability density function, which has many local minimum. 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). Its algorithm is coded in Mathematica and then tested for estimating parameters of noisy sinusoids. Computer simulations support its effectiveness and demonstrate its performance, according to Cramér-Rao lower bound for sufficiently high signal-to-noise ratios and data lengths.
Keywords: Bayesian Estimation, Harmonic Sinusoidal Signals, Parallel Tempering, Markov Chain Monte Carlo,
EXTENSION of the file: .doc
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