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A robust model for spatiotemporal dependencies

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

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Abstract

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
Date:2008
Institutions:Biology, Preclinical Medicine > Institut für Biophysik und physikalische Biochemie > Prof. Dr. Elmar Lang
Identification Number:
ValueType
10.1016/j.neucom.2007.06.012DOI
Classification:
NotationType
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
Status:Published
Refereed:Unknown
Created at the University of Regensburg:Unknown
Item ID:16912
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