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Bayesian estimation of sinusoidal signals via parallel tempering
| Content Provider | Semantic Scholar |
|---|---|
| Author | Cevri, Mehmet Üstündaǧ, Dursun |
| Copyright Year | 2009 |
| 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. |
| Starting Page | 67 |
| Ending Page | 72 |
| Page Count | 6 |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.wseas.us/e-library/conferences/2009/istanbul/SIP-WAV/SIP-WAV-11.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
