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Denoising using local ICA and a generalized eigendecomposition with time-delayed signals

Gruber, P. and Stadlthanner, K. and Tomé, A. and Teixeira, A. and Theis, Fabian J. and Puntonet, Carlos G. and Lang, Elmar (2004) Denoising using local ICA and a generalized eigendecomposition with time-delayed signals. In: Puntonet, Carlos G., (ed.) Independent component analysis and blind signal separation: fifth international conference, ICA 2004, Granada, Spain, September 22 - 24, 2004; proceedings. Lecture Notes in Computer Science, 3195. Springer, Berlin, pp. 993-1000.

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Abstract

We present denoising algorithms based on either local independent component analysis (ICA) and a minimum description length (MDL) estimator or a generalized eigenvalue decomposition (GEVD) using a matrix pencil of time-delayed signals. Both methods are applied to signals embedded in delayed coordinates in a high-dim feature space OHgr and denoising is achieved by projecting onto a lower ...

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Item Type:Book Section
Date:2004
Institutions:Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang
Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang > Arbeitsgruppe Dr. Fabian Theis
Projects:Graduiertenkolleg Nichtlinearität und Nichtgleichgewicht
Identification Number:
ValueType
10.1007/978-3-540-30110-3_125DOI
Related URLs:
URLURL Type
http://www.springerlink.com/content/p52wb08l3wefhtux/Publisher
Subjects:500 Science > 530 Physics
500 Science > 570 Life sciences
Status:Published
Refereed:Yes, this version has been refereed
Created at the University of Regensburg:Yes
Owner: Redakteur Physik
Deposited On:20 Mar 2007
Last Modified:29 Sep 2010 09:45
Item ID:1599
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