Time-frequency and time-scale analysis of deformed stationary processes, with application to non-stationary sound modeling

摘要

A class of random non-stationary signals termed timbrex dynamics is introduced and studied. These signals are obtained by non-linear transformations of stationary random Gaussian signals, in such a way that the transformation can be approximated by translations in an appropriate representation domain. In such situations, approximate maximum likelihood estimation techniques can be derived, which yield simultaneous estimation of the transformation and the power spectrum of the underlying stationary signal.