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Analysing ICA component by injection noise

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons83954

Harmeling,  S
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons84096

Müller,  K-R
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zitation

Harmeling, S., Meinecke, F., & Müller, K.-R. (2003). Analysing ICA component by injection noise. Proceedings of the 4th International Symposium on Independent Component Analysis and Blind Signal Separation (ICA 2003), 149-154.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-DCB3-1
Zusammenfassung
Usually, noise is considered to be destructive. We present a new method that constructively injects noise to assess the reliability and the group structure of empirical ICA components. Simulations show that the true root-mean squared angle distances between the real sources and some source estimates can be approximated by our method. In a toy experiment, we see that we are also able to reveal the underlying group structure of extracted ICA components. Furthermore, an experiment with fetal ECG data demonstrates that our approach is useful for exploratory data analysis of real-world data.