|Time-frequency and time-scale analysis of deformed stationary processes, with application to non-stationary sound modeling |
(Article) Publié: Applied And Computational Harmonic Analysis, vol. p. (2016)
Ref HAL: hal-01094835_v2
Ref Arxiv: 1510.08240
Ref. & Cit.: NASA ADS
Exporter : BibTex | endNote
A class of random non-stationary signals termed timbre×dynamics is introduced and studied. These signals are obtained by non-linear transformations of sta-tionary 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 de-rived, which yield simultaneous estimation of the transformation and the power spectrum of the underlying stationary signal. This paper focuses on the case of modulation and time warping of station-ary signals, and proposes and studies estimation algorithms (based on time-frequency and time-scale representations respectively) for these quantities of interest. The proposed approach is validated on numerical simulations on synthetic signals, and examples on real life car engine sounds.