Title :
Gibbs random sequences Bayes estimation based on stochastic relaxation
Author :
Vasyukov, Vasiliy ; Goleshchikhin, Denis
Author_Institution :
Novosibirsk State Tech. Univ., Russia
Abstract :
An opportunity of Metropolis-Hastings stochastic relaxation procedure application for optimal Gibbs random message interpolation is investigated. A conditional-Gaussian random sequence as an example of Gibbs sequence observed in white Gaussian noise is used as message model. Such models are used, e.g. for speech signal description. The basic Metropolis-Hastings algorithm is described and some experimental results are presented
Keywords :
Bayes methods; Gaussian noise; interpolation; parameter estimation; probability; signal processing; Bayes estimation; Gaussian noise; Gibbs random sequences; Metropolis-Hastings algorithm; message interpolation; parameter estimation; probability; stochastic relaxation; Gaussian noise; Interpolation; Parameter estimation; Probability distribution; Proposals; Random sequences; Signal processing algorithms; Speech; Stochastic processes; Stochastic resonance;
Conference_Titel :
Science and Technology, 2000. KORUS 2000. Proceedings. The 4th Korea-Russia International Symposium on
Conference_Location :
Ulsan
Print_ISBN :
0-7803-6486-4
DOI :
10.1109/KORUS.2000.866016
