Facultad de Ciencias
Universidad Autónoma del Estado de Morelos, México
Consequently, detailed information about the correlation structure of the multivariate data set is imprinted into the dynamics of the eigenvalues and into the structure of the corresponding eigenvectors.
The performance of the technique is demonstrated by application to articicially created datasets and electroencephalographic recordings of eplileptic patients with the aim to detect and characterizea possible precursor activity. A comparison with the Independent Component Analysis is provided. The high sensitivity and the comparatively small computational effort recommend it for application to the analysis of complex, spatially extended, nonstationary systems.
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Erstellt von: Anke Weinberger (2004-06-02). Wartung durch: Anke Weinberger (2004-06-21). |