PuSH - Publikationsserver des Helmholtz Zentrums München: Soft dimension reduction for ICA by joint diagonalization on the Stiefel manifold.

Navigation

Startseite

English

Recherche

Erweiterte Suche

Durchblättern nach ...

... Zeitschriften

... Publikationstypen

... Forschungsdaten

... Erscheinungsjahr

Publikationen im Überblick

Hilfe & Kontakt

Ansprechpartner

Hilfe

Datenschutz

Theis, F.J. ; Cason, T.P.* ; Absil, P.A.*

Soft dimension reduction for ICA by joint diagonalization on the Stiefel manifold.

In: Independent Component Analysis and Signal Separation. Berlin [u.a.]: Springer, 2009. 354-361 (Lect. Notes Comput. Sc. ; 5441)

DOI

Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.

Abstract
Metriken
Zusatzinfos

Joint diagonalization for ICA is often performed on the orthogonal group after a pre-whitening step. Here we assume that we only want to extract a few sources after pre-whitening, and hence work on the Stiefel manifold of $p$-frames in $R^n$. The resulting method does not only use second-order statistics to estimate the dimension reduction and is therefore denoted as soft dimension reduction. We employ a trust-region method for minimizing the cost function on the Stiefel manifold. Applications to a toy example and functional MRI data show a higher numerical efficiency, especially when $p$ is much smaller than $n$, and more robust performance in the presence of strong noise than methods based on pre-whitening.

Altmetric

Weitere Metriken?

[➜Einloggen]