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A robust model for spatiotemporal dependencies

Theis, Fabian J. and Gruber, Peter and Keck, Ingo R. and Lang, Elmar (2008) A robust model for spatiotemporal dependencies. Neurocomputing 71 (10-12), pp. 2209-2216.

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Real-world data sets such as recordings from functional magnetic resonance imaging (fMRI) often possess both spatial and temporal structures. Here, we propose an algorithm including such spatiotemporal information into the analysis, and reduce the problem to the joint approximate diagonalization of a set of autocorrelation matrices. We demonstrate the feasibility of the algorithm by applying it to fMRI analysis, where previous approaches are outperformed considerably.

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Item type:Article
Institutions:Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang
Identification Number:
07.05.Kf; 87.61.−c; 05.40.−a; 05.45.TpPACS
Keywords:Blind source separation; Independent component analysis; Functional magnetic resonance imaging; Autodecorrelation
Dewey Decimal Classification:500 Science > 570 Life sciences
Created at the University of Regensburg:Unknown
Deposited on:05 Oct 2010 06:36
Last modified:05 Oct 2010 06:36
Item ID:16912
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