PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Interacting Source Analysis- Identifying interactions in mixed and noisy complex systems
Frank Meinecke, Andreas Ziehe, Guido Nolte and Klaus-Robert Müller
In: ICA Research Network International Workshop, 18-19 Sep 2006, Liverpool, U.K..

Abstract

We present a technique which identifies interacting subsystems of a complex system from multi-channel data if the recordings are an unknown linear and instantaneous mixture of the true sources. The method is valid for arbitrary noise structure. For this, a new blind source separation (BSS) technique is proposed that diagonalizes antisymmetrized cross-correlation or cross-spectral matrices. The resulting decomposition finds truly interacting subsystems blindly and suppresses any spurious interaction stemming from the mixture.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Brain Computer Interfaces
Theory & Algorithms
ID Code:2426
Deposited By:Andreas Ziehe
Deposited On:22 November 2006