This paper studies probability density estimation on the Siegel space. The Siegel space is a
generalization of the hyperbolic space. Its Riemannian metric provides an interesting …

The objective of this thesis is the classification of complex valued stationary centered
Gaussian autoregressive time series. We study the case of one-dimensional time series as …

Here we propose a method to classify radar clutter from radar data using an unsupervised
classification algorithm. The data will be represented by Positive Definite Hermitian Toeplitz …

This paper deals with unsupervised radar clutter clustering to characterize pathological
clutter based on their Doppler fluctuations. Operationally, being able to recognize …

Here we propose a method to classify radar clutter from radar data using a non-supervised
classification algorithm. Thus new radars will be able to use the experience of other radars …

For classification of Radar micro-Doppler signature by Machine Learning techniques, first
step consists in coding the data in well adapted metric space. We propose a new approach …

This paper describes new geometrical approaches to define the statistics of spatio-temporal
measurements of the states of an electromagnetic wave, by using the notion of" average" …

In this paper we propose a method to classify radar clutter from radar data using a non-
supervised classification algorithm. As a final objective, new radars will therefore be able to …

Radar sea clutter inhomogeneity in range is characterized by Doppler mean and spectrum
width variations. We propose a new approach for robust statistical density estimation and …

The aim is to describe new geometric approaches to define the statistics of spatio-temporal
and polarimetric measurements of the states of an electromagnetic wave, using the works of …