Work

Blind Separation of Sources: Methods, Assumptions and Applications

Year: 2000

Type: article

Abstract: The blind separation of sources is a recent and important problem in signal processing. Since 1984, it has been studied by many authors whilst many algorithms have been proposed. In this paper, the description of the problem, its assumptions, its currently applications and some algorithms and ideas are discussed. keywords: independent component analysis (ICA), contrast function, Kullback-Leibner divergence, prediction error, sub-space methods, decorrelation, high order statistics, whitening, Mutual-Information, likelihood maximization, conjoint diagonalization.

Authors: Ali Mansour, Allan Kardec Barros, Noboru Ohnishi

Language: English

Topic: Blind Source Separation Techniques

Subfield: Signal Processing

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W1574130859

FWCI: 6.252

Cites: 103

Cited by: 76

Related to: 10