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| Research article summary (published 29 Nov 2002): |
A resampling approach to estimate the stability of one-dimensional or multidimensional independent components.
Full Abstract
When applying unsupervised learning techniques in biomedical data analysis, a key question is whether the estimated parameters of the studied system are reliable. In other words, can we assess the quality of the result produced by our learning technique? We propose resampling methods to tackle this question and illustrate their usefulness for blind-source separation (BSS). We demonstrate that our proposed reliability estimation can be used to discover stable one-dimensional or multidimensional independent components, to choose the appropriate BSS-model, to enhance significantly the separation performance, and, most importantly, to flag components that carry physical meaning. Application to different biomedical testbed data sets (magnetoencephalography (MEG)/electrocardiography (ECG)-recordings) underline the usefulness of our approach.
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Author information
Author/s: Meinecke, Frank (F); Ziehe, Andreas (A); Kawanabe, Motoaki (M); Müller, Klaus-Robert (KR);
Affiliation: Department of Physics, University of Potsdam, 14469 Potsdam, Germany. frank.meinecke@first.fraunhofer.de
Journal and publication information
Publication Type: Evaluation Studies; Journal Article; Research Support, Non-U.S. Gov't; Validation Studies
Journal: IEEE transactions on bio-medical engineering (IEEE Trans Biomed Eng), published in United States. (Language: eng)
Reference: 2002-Dec; vol 49 (issue 12 Pt 2) : pp 1514-25
Dates: Created 2003/01/28; Completed 2003/04/16; Revised 2006/11/15;
PMID: 12549733, status: MEDLINE (last retrieval date: 11/6/2008)
Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.
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