4 papers
Synthesis-based time-scale transforms for non-stationary signals
Adrien Meynard, Bruno Torrésani
This paper deals with the modeling of non-stationary signals, from the point of view of signal synthesis. A class of random, non-stationary signals, generated by synthesis from a r…
Time-scale synthesis for locally stationary signals
Adrien Meynard, Bruno Torrésani
We develop a timescale synthesis-based probabilistic approach for the modeling of locally stationary signals. Inspired by our previous work, the model involves zero-mean, complex G…
A Bayesian model for microarray datasets merging
Marie-Christine Roubaud, Bruno Torrésani
The aggregation of microarray datasets originating from different studies is still a difficult open problem. Currently, best results are generally obtained by the so-called meta-an…
Analyse discriminante matricielle descriptive. Application a l'étude de signaux EEG
Juliette Spinnato, Marie-Christine Roubaud, Margaux Perrin +4
We focus on the descriptive approach to linear discriminant analysis for matrix-variate data in the binary case. Under a separability assumption on row and column variability, the…