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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 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.