Analysing ICA component by injection noise
2003
Conference Paper
ei
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.
Author(s): | Harmeling, S. and Meinecke, F. and Müller, K-R. |
Book Title: | ICA 2003 |
Journal: | Proceedings of the 4th International Symposium on Independent Component Analysis and Blind Signal Separation (ICA 2003) |
Pages: | 149-154 |
Year: | 2003 |
Month: | April |
Day: | 0 |
Editors: | Amari, S.-I. , A. Cichocki, S. Makino, N. Murata |
Department(s): | Empirical Inference |
Bibtex Type: | Conference Paper (inproceedings) |
Event Name: | 4th International Symposium on Independent Component Analysis and Blind Signal Separation |
Event Place: | Nara, Japan |
Digital: | 0 |
Language: | en |
Organization: | Max-Planck-Gesellschaft |
School: | Biologische Kybernetik |
Links: |
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BibTex @inproceedings{6358, title = {Analysing ICA component by injection noise}, author = {Harmeling, S. and Meinecke, F. and M{\"u}ller, K-R.}, journal = {Proceedings of the 4th International Symposium on Independent Component Analysis and Blind Signal Separation (ICA 2003)}, booktitle = {ICA 2003}, pages = {149-154}, editors = {Amari, S.-I. , A. Cichocki, S. Makino, N. Murata}, organization = {Max-Planck-Gesellschaft}, school = {Biologische Kybernetik}, month = apr, year = {2003}, doi = {}, month_numeric = {4} } |