This paper presents an application of ICA to astronomical imaging. A first section describes the astrophysical context and motivates the use of source separation ideas. A second section describes our approach to the problem: the use of a noisy Gaussian stationary model. This technique uses spectral diversity and take explicitly into account contamination by additive noise. Preliminary and extremely encouraging results on realistic synthetic signals and on real data will be presented at the conferenc
Aims. The separation of foreground contamination from cosmic microwave background (CMB) observations...
International audienceWe present in this paper a new Bayesian semi-blind approach for foreground rem...
We describe different methods for estimating the bispectrum of Cosmic Microwave Background data. In ...
This paper presents an application of ICA to astro-nomical imaging. A first section describes the as...
We implement an independent component analysis (ICA) algorithm to separate signals of different orig...
submitted to ICA 2004 conference on Independent Component Analysis - Coll. Planck-HFIThis paper pres...
The main topic of this thesis is the analysis of Cosmic Microwave Background (CMB) data. In particul...
We present a new, fast, algorithm for the separation of astrophysical components superposed in maps ...
We present a new, fast, algorithm for the separation of astrophysical components superposed in maps ...
We review issues and methods for diffuse component separation in the context of Cosmic Microwave Bac...
We present a blind multi-detector multi-component spectral matching method for all sky observations ...
International audienceCosmology concerns itself with the fundamental questions about the formation, ...
The detection and characterization of the B mode of cosmic microwave background (CMB) polarization a...
The work described in this Thesis is related to the PLANCK mission, scheduled for launch in 2008, wh...
We present the application of the fast independent component analysis (fastica) technique for blind ...
Aims. The separation of foreground contamination from cosmic microwave background (CMB) observations...
International audienceWe present in this paper a new Bayesian semi-blind approach for foreground rem...
We describe different methods for estimating the bispectrum of Cosmic Microwave Background data. In ...
This paper presents an application of ICA to astro-nomical imaging. A first section describes the as...
We implement an independent component analysis (ICA) algorithm to separate signals of different orig...
submitted to ICA 2004 conference on Independent Component Analysis - Coll. Planck-HFIThis paper pres...
The main topic of this thesis is the analysis of Cosmic Microwave Background (CMB) data. In particul...
We present a new, fast, algorithm for the separation of astrophysical components superposed in maps ...
We present a new, fast, algorithm for the separation of astrophysical components superposed in maps ...
We review issues and methods for diffuse component separation in the context of Cosmic Microwave Bac...
We present a blind multi-detector multi-component spectral matching method for all sky observations ...
International audienceCosmology concerns itself with the fundamental questions about the formation, ...
The detection and characterization of the B mode of cosmic microwave background (CMB) polarization a...
The work described in this Thesis is related to the PLANCK mission, scheduled for launch in 2008, wh...
We present the application of the fast independent component analysis (fastica) technique for blind ...
Aims. The separation of foreground contamination from cosmic microwave background (CMB) observations...
International audienceWe present in this paper a new Bayesian semi-blind approach for foreground rem...
We describe different methods for estimating the bispectrum of Cosmic Microwave Background data. In ...