Theis, Fabian J. and Gruber, Peter and Keck, Ingo R. and Lang, Elmar W. (2008) A robust model for spatiotemporal dependencies. NEUROCOMPUTING, 71 (10-12). pp. 2209-2216. ISSN 0925-2312, 1872-8286
Full text not available from this repository. (Request a copy)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. (C) 2008 Elsevier B.V. All rights reserved.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | INDEPENDENT COMPONENT ANALYSIS; BLIND SEPARATION; FMRI DATA; NONSTATIONARY SOURCES; ALGORITHM; MIXTURES; SIGNALS; blind source separation; independent component analysis; functional magnetic resonance imaging; autodecorrelation |
| Subjects: | 500 Science > 570 Life sciences |
| Divisions: | 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 |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 29 Oct 2020 13:22 |
| Last Modified: | 29 Oct 2020 13:22 |
| URI: | https://pred.uni-regensburg.de/id/eprint/30845 |
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