Injecting noise for analysing the stability of ICA components

Stefan Harmeling, Frank Meinecke, Klaus Robert Müller

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)255-266
Number of pages12
JournalSignal Processing
Issue number2
Publication statusPublished - 2004 Feb


  • ICA
  • Noise injection
  • Stability

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering


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