F
Frédéric Pascal
Researcher at Université Paris-Saclay
Publications - 205
Citations - 3340
Frédéric Pascal is an academic researcher from Université Paris-Saclay. The author has contributed to research in topics: Covariance matrix & Estimator. The author has an hindex of 27, co-authored 194 publications receiving 2982 citations. Previous affiliations of Frédéric Pascal include École normale supérieure de Cachan & University of Paris-Sud.
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Covariance Structure Maximum-Likelihood Estimates in Compound Gaussian Noise: Existence and Algorithm Analysis
TL;DR: The derivation is based on some likelihood functions general properties like homogeneity and can be easily adapted to other recursive contexts and shows the convergence of this recursive scheme, ensured whatever the initialization.
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Performance Analysis of Covariance Matrix Estimates in Impulsive Noise
TL;DR: A statistical study of the main covariance matrix estimates used in the literature is performed through bias analysis, consistency, and asymptotic distribution to compare the performance of the estimates and to establish simple relationships between them.
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Convergence of Adaptive Discontinuous Galerkin Approximations of Second-Order Elliptic Problems
TL;DR: A residual-type a posteriori error estimator is introduced and analyzed for a discontinuous Galerkin formulation of a model second-order elliptic problem with Dirichlet-Neumann-type boundary conditions and shown to achieve any specified error level in the energy norm in a finite number of cycles.
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Parameter Estimation For Multivariate Generalized Gaussian Distributions
TL;DR: It is proved that the maximum likelihood estimator (MLE) of the scatter matrix exists and is unique up to a scalar factor, for a given shape parameter β ∈ (0,1).
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Coherency Matrix Estimation of Heterogeneous Clutter in High-Resolution Polarimetric SAR Images
TL;DR: This paper presents an application of the recent advances in the field of spherically invariant random vector (SIRV) modeling for coherency matrix estimation in heterogeneous clutter for POLSAR classification with results of entropy/alpha/anisotropy decomposition and unsupervised classification.