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  Injecting noise for analysing the stability of ICA components

Harmeling, S., Meinecke, F., & Müller, K.-R. (2004). Injecting noise for analysing the stability of ICA components. Signal Processing, 84(2), 255-266. doi:10.1016/j.sigpro.2003.10.009.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-D9CF-C Version Permalink: http://hdl.handle.net/21.11116/0000-0005-4F7D-8
Genre: Journal Article

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Harmeling, S1, Author              
Meinecke, F, Author
Müller, K-R1, Author              
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1External Organizations, ou_persistent22              

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 Abstract: Usually, noise is considered to be destructive. We present a new method that constructively injects noise to assess the reliability and the grouping structure of empirical ICA component estimates. Our method can be viewed as a Monte-Carlo-style approximation of the curvature of some performance measure at the solution. Simulations show that the true root-mean-squared angle distances between the real sources and the source estimates can be approximated well by our method. In a toy experiment, we see that we are also able to reveal the underlying grouping structure of the extracted ICA components. Furthermore, an experiment with fetal ECG data demonstrates that our approach is useful for exploratory data analysis of real-world data.

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 Dates: 2004-02
 Publication Status: Published in print
 Pages: -
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 Rev. Method: -
 Identifiers: DOI: 10.1016/j.sigpro.2003.10.009
BibTex Citekey: 6355
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Title: Signal Processing
Source Genre: Journal
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Publ. Info: New York, NY : Elsevier
Pages: - Volume / Issue: 84 (2) Sequence Number: - Start / End Page: 255 - 266 Identifier: ISSN: 0165-1684
CoNE: https://pure.mpg.de/cone/journals/resource/954925481601