Two pairwise iterative schemes for high dimensional blind source separation

Two Pairwise Iterative Schemes For High Dimensional Blind Source Separation

paper addresses the high dimensionality problem in blind source separation (BSS), where the number of sources is greater than two. Two pairwise iterative schemes are proposed to tackle this high dimensionality problem. The two pairwise schemesrealize non-parametric independent component analysis (ICA) algorithms based on a new high-performance Convex Cauchy–Schwarz Divergence (CCS-DIV). These t...

An Iterative Inversion Method For Blind Source Separation

Comparison of Blind Source Separation Methods based on Iterative Algorithms

In this paper some approaches to detect signal streams of a multi layer transmission system are presented. We will focus on blind algorithms for the separation of the data stream and improve their performance in an iterative way in order to gain nearly the same performance as with a known channel matrix. The overall algorithm will remain blind and does not need any training data.

A Soft-Constrained Dynamic Iterative Method of Blind Source Separation

The blind source separation problem arises when one attempts to recover source signals from their linear mixtures without detailed knowledge of the mixing process. Solutions are nonunique and have degrees of freedom in scaling and permutation. One may impose equality (hard) constraints to fix these scaling parameters; however, small divisor problems may appear. In this paper, an iterative metho...

An iterative inversion approach to blind source separation

In this paper we present an iterative inversion (II) approach to blind source separation (BSS). It consists of a quasi-Newton method for the resolution of an estimating equation obtained from the implicit inversion of a robust estimate of the mixing system. The resulting learning rule includes several existing algorithms for BSS as particular cases giving them a novel and unified interpretation...