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Blind source separation methods and application to remote sensing
Thèse en co-tutelle internationale Franco-Algérienne -
Image decomposition and separation using sparse representations: an overview
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An overview of inverse problem regularization using sparsity
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Sensor Networks for Underwater Ecosystem Monitoring & Port Surveillance Systems
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Separation of instantaneous mixtures of dependent sources using classical ICA...
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Nonnegative Joint Diagonalization by Congruence Based on LU Matrix Factorization
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Blind source separation methods for hyperspectral imaging. Application to urb...
In this work, we developed Blind Source Separation methods (BSS) for hyperspectral images, concerning two applications : urban remote sensing and astrophysics. The... -
Iterative Algorithms
The present chapter surveys computational algorithms for solving the independent component analysis (ICA) problem. Most of these algorithms rely on gradient or Newton... -
Generalized mutual information approach to multichannel blind deconvolution
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Prediction of treatment response and the effect of independent component neur...
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Ecosystem Monitoring and Port Surveillance Systems
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Semi-Blind Source Separation in a Multi-User Transmission System with Interfe...
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Jacobi-like nonnegative joint diagonalization by congruence
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Non-Negative Blind Source Separation Algorithm Based on Minimum Aperture Simp...
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Audiovisual Speech Source Separation: An overview of key methodologies
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Error Analysis of Low-rank Three-Way Tensor Factorization Approach to Blind S...
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Nonlinear blind source separation using kernels
Article dans revue scientifique avec comité de lecture. -
Hidden Markov chains and unsupervised source separation
The restoration problem is usually encountered in various domains and in particular in signal and image processing. It consists in retrieving original data from a set... -
Principal component analysis and perturbation theory-based robust damage dete...
International audience
