Bayesian estimation of instantaneous frequency

Abstract

The problem addressed in this paper is the Bayesian estimation of the instantaneous frequency for parametric nonstationary processes. We carry out Bayesian inference on the unknown parameters using powerful stochastic algorithms, the Markov chain Monte Carlo methods. Applications of such techniques to several models are presented and results of a simulation for one of those models are presented.