Injecting noise for analysing the stability of ICA components

Harmeling, S; Meinecke, F; Müller, K-R

doi:10.1016/j.sigpro.2003.10.009

Item

ITEM ACTIONSEXPORT

Add to Basket

Local TagsRelease HistoryDetailsSummary

Released

Journal Article

Injecting noise for analysing the stability of ICA components

MPS-Authors

There are no MPG-Authors in the publication available

External Resource

https://www.sciencedirect.com/science/article/pii/S0165168403002743
(Publisher version)

Fulltext (restricted access)

There are currently no full texts shared for your IP range.

Fulltext (public)

There are no public fulltexts stored in PuRe

Supplementary Material (public)

There is no public supplementary material available

Citation

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.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-D9CF-C

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.