This thesis addresses problems in the field of time-varying, non-Gaussian, non-linear signal processing. It concentrates on developing results in the areas of time-frequency signal analysis and higher-order spectra which are linked by the developing area of time-varying higher-order spectra. Motivation comes from applying procedures developed to underwater acoustic signals. Reviews of time-frequency analysis and higher-order spectra precede the research contributions. Three appendices cover: a review of the multiple-window spectrum estimation method, an improved procedure for computing analytic signals frequently used in time-frequency signal analysis, and an updated approach for computing Slepian sequences necessary for the multiple-windo...
This work investigates methods for the analysis and synthesis of nonstationary signals using time-fr...
International audienceThis work concerns the analysis of non-stationary signals using Recurrence Plo...
Thesis (Master's)--University of Washington, 2014A common assumption used in statistical signal proc...
A class of Polynomial time-frequency distributions has been recently proposed. It achieves the highe...
Non-parametric time-frequency methods for spectral estimation are increasingly used in the analysis ...
International audienceThis paper proposes a parameters estimation algorithm for signals composed of ...
This thesis focuses on statistical methods for non-stationary signals. The methods considered or dev...
The broad-based goal of this thesis is to understand, detect, identify and quantify the abstract ent...
This thesis deals with the problems of modelling, interpretation and estimation of 'non-stationary' ...
The bias-variance trade-off is an important issue is spectrum estimation. In 1982, Thomson introduce...
Sonar signal processing comprises of a large number of signal processing algorithms for implementing...
A new time-varying autoregressive modeling has been proposed as a tool for time-frequency analysis o...
International audienceA real environment identification system is based on observations analysis whi...
This thesis deals with two related subjects: adaptive algorithms in signal processing and system ide...
Abstract—Time-frequency representations constitute the main tool for analysis of nonstationary signa...
This work investigates methods for the analysis and synthesis of nonstationary signals using time-fr...
International audienceThis work concerns the analysis of non-stationary signals using Recurrence Plo...
Thesis (Master's)--University of Washington, 2014A common assumption used in statistical signal proc...
A class of Polynomial time-frequency distributions has been recently proposed. It achieves the highe...
Non-parametric time-frequency methods for spectral estimation are increasingly used in the analysis ...
International audienceThis paper proposes a parameters estimation algorithm for signals composed of ...
This thesis focuses on statistical methods for non-stationary signals. The methods considered or dev...
The broad-based goal of this thesis is to understand, detect, identify and quantify the abstract ent...
This thesis deals with the problems of modelling, interpretation and estimation of 'non-stationary' ...
The bias-variance trade-off is an important issue is spectrum estimation. In 1982, Thomson introduce...
Sonar signal processing comprises of a large number of signal processing algorithms for implementing...
A new time-varying autoregressive modeling has been proposed as a tool for time-frequency analysis o...
International audienceA real environment identification system is based on observations analysis whi...
This thesis deals with two related subjects: adaptive algorithms in signal processing and system ide...
Abstract—Time-frequency representations constitute the main tool for analysis of nonstationary signa...
This work investigates methods for the analysis and synthesis of nonstationary signals using time-fr...
International audienceThis work concerns the analysis of non-stationary signals using Recurrence Plo...
Thesis (Master's)--University of Washington, 2014A common assumption used in statistical signal proc...