Neural Comp. NEW Faster Access
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Van Hulle, M. M.
Right arrow Search for Related Content
PubMed
Right arrow Articles by Van Hulle, M. M.
(Neural Computation. 2007;20:964-973.)
© 2007 The MIT Press

Letter

Constrained Subspace ICA Based on Mutual Information Optimization Directly

Marc M. Van Hulle

marc{at}neuro.kuleuven.be K. U. Leuven, Laboratorium voor Neuro- en Psychofysiologie, B-3000 Leuven, Belgium

We introduce a new approach to constrained independent component analysis (ICA) by formulating the original, unconstrained ICA problem as well as the constraints in mutual information terms directly. As an estimate of mutual information, a robust version of the Edgeworth expansion is used, on which gradient descent is performed. As an application, we consider the extraction of both the mother and the fetal antepartum electrocardiograms (ECG) from multielectrode cutaneous recordings on the mother's thorax and abdomen.






HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
J COGNITIVE NEUROSCIENCE NEURAL COMPUTATION MIT PRESS JOURNALS
Copyright © 2007 by The MIT Press.