Articolo in rivista, 2005, ENG, 10.1155/ASP.2005.2400

Separation of correlated astrophysical sources using multiple-lag data covariance matrices

Bedini L.; Herranz D.; Salerno E.; Baccigalupi C.; Kuruoglu E.E.; Tonazzini A.

CNR ISTI SISSA (Baccigalupi)

This paper proposes a new strategy to separate astrophysical sources that are mutually correlated. This strategy is based on second order statistics and exploits prior information about the possible structure of the mixing matrix. Unlike ICA blind separation approaches, where the sources are assumed mutually independent and no prior knowledge is assumed about the mixing matrix, our strategy allows the independence assumption to be relaxed and performs the separation of even significantly correlated sources. Besides the mixing matrix, our strategy is also capable to evaluate the source covariance functions at several lags. Moreover, once the mixing parameters have been identified, a simple deconvolution can be used to estimate the probability density functions of the source processes. To benchmark our algorithm, we used a database that simulates the one expected from the instruments that will operate onboard ESA's Planck Surveyor Satellite to measure the CMB anisotropies all over the celestial sphere.

EURASIP journal on applied signal processing 2005 (15), pp. 2400–2412

Keywords

J.2 Physical Sciences and Engineering, I.4 Image processing and computer vision

CNR authors

Bedini Luigi, Kuruoglu Ercan Engin, Salerno Emanuele, Tonazzini Anna

CNR institutes

ISTI – Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"

ID: 43838

Year: 2005

Type: Articolo in rivista

Creation: 2009-06-16 00:00:00.000

Last update: 2012-06-01 09:59:25.000

External links

OAI-PMH: Dublin Core

OAI-PMH: Mods

OAI-PMH: RDF

DOI: 10.1155/ASP.2005.2400

External IDs

CNR OAI-PMH: oai:it.cnr:prodotti:43838

DOI: 10.1155/ASP.2005.2400

ISI Web of Science (WOS): 000234953500002

Scopus: 2-s2.0-31444447309