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Spatiotemporal blind source separation using double-sided approximate joint diagonalization

Theis, Fabian J. ; Gruber, Peter ; Keck, I. R. ; Meyer-Bäse, A. ; Lang, Elmar


Abstract

In independent component analysis (ICA) the common task is to achieve either spatial or temporal independence by linearly mapping into a feature space. If the data possesses both spatial and temporal structures such as a sequence of images or 3d-scans taken at fixed time intervals, we can require the transformed data to be as independent as possible in both domains. First introduced by Stone ...

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