Independent Component Analysis and Blind Signal Separation | Zendy

G. Patanchon | Zendy; Jacques Delabrouille | Zendy; J.-F. Cardoso | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Independent Component Analysis and Blind Signal Separation

Author(s) -

G. Patanchon,

Jacques Delabrouille,

J.-F. Cardoso

Publication year - 2004

Publication title -

lecture notes in computer science

Language(s) - English

Resource type - Book series

SCImago Journal Rank - 0.249

H-Index - 400

eISSN - 1611-3349

pISSN - 0302-9743

DOI - 10.1007/b100528

Subject(s) - blind signal separation , independent component analysis , cmb cold spot , cosmic microwave background , component (thermodynamics) , separation (statistics) , computer science , spectral density , signal (programming language) , source separation , astrophysics , pattern recognition (psychology) , artificial intelligence , physics , algorithm , telecommunications , optics , machine learning , channel (broadcasting) , thermodynamics , anisotropy , programming language

submitted to ICA 2004 conference on Independent Component Analysis - Coll. Planck-HFIThis paper presents and discusses the application of blind source separation to astrophysical data obtained with the WMAP satellite. Blind separation permits to identify and isolate a component compatible with CMB emission, and to measure both its spatial power spectrum and its emission law. Both are found to be compatible with the present concordance cosmological model. This application demonstrates the usefulness of blind ICA for cosmological applications

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research