An Algebraic Non Orthogonal Joint Block Diagonalization Algorithm for Blind Separation of Convolutive Mixtures of Sources

Autor:	El Mostafa Fadaili, Eric Moreau, Nadège Thirion-Moreau, Abdellah Adib, Hicham Ghennioui
Rok vydání:	2007
Předmět:	Least mean squares filter symbols.namesake Gaussian noise MathematicsofComputing_NUMERICALANALYSIS symbols Source separation Algebraic number Blind signal separation Algorithm Independent component analysis Mathematics Block (data storage) Orthogonal diagonalization
Zdroj:	Independent Component Analysis and Signal Separation ISBN: 9783540744931 ICA
DOI:	10.1007/978-3-540-74494-8_25
Popis:	This paper deals with the problem of the blind separation of convolutive mixtures of sources. We present a novel method based on a new non orthogonal joint block diagonalization algorithm (NO - JBD) of a given set of matrices. The main advantages of the proposed method are that it is more general and a preliminary whitening stage is no more compulsorily required. The proposed joint block diagonalization algorithm is based on the algebraic optimization of a least mean squares criterion. Computer simulations are provided in order to illustrate the effectiveness of the proposed approach in three cases: when exact block-diagonal matrices are considered, then when they are progressively perturbed by an additive Gaussian noise and finally when estimated correlation matrices are used. A comparison with a classical orthogonal joint block-diagonalization algorithm is also performed, emphasizing the good performances of the method.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::d42ba164552828a20a9b8cbb56657b16 https://doi.org/10.1007/978-3-540-74494-8_25 Zobrazit plný text záznamu