Measuring Non-Gaussianity by Phi-Transformed and Fuzzy Histograms
Joint Authors
Böhm, Christian
Thai, Son Mai
Plant, Claudia
Shao, Junming
Theis, Fabian J.
Meyer-Baese, Anke
Source
Advances in Artificial Neural Systems
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-06-04
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Information Technology and Computer Science
Abstract EN
Independent component analysis (ICA) is an essential building block for data analysis in many applications.
Selecting the truly meaningful components from the result of an ICA algorithm, or comparing the results of different algorithms, however, is nontrivial problems.
We introduce a very general technique for evaluating ICA results rooted in information-theoretic model selection.
The basic idea is to exploit the natural link between non-Gaussianity and data compression: the better the data transformation represented by one or several ICs improves the effectiveness of data compression, the higher is the relevance of the ICs.
We propose two different methods which allow an efficient data compression of non-Gaussian signals: Phi-transformed histograms and fuzzy histograms.
In an extensive experimental evaluation, we demonstrate that our novel information-theoretic measures robustly select non-Gaussian components from data in a fully automatic way, that is, without requiring any restrictive assumptions or thresholds.
American Psychological Association (APA)
Plant, Claudia& Thai, Son Mai& Shao, Junming& Theis, Fabian J.& Meyer-Baese, Anke& Böhm, Christian. 2012. Measuring Non-Gaussianity by Phi-Transformed and Fuzzy Histograms. Advances in Artificial Neural Systems،Vol. 2012, no. 2012, pp.1-13.
https://search.emarefa.net/detail/BIM-511750
Modern Language Association (MLA)
Plant, Claudia…[et al.]. Measuring Non-Gaussianity by Phi-Transformed and Fuzzy Histograms. Advances in Artificial Neural Systems No. 2012 (2012), pp.1-13.
https://search.emarefa.net/detail/BIM-511750
American Medical Association (AMA)
Plant, Claudia& Thai, Son Mai& Shao, Junming& Theis, Fabian J.& Meyer-Baese, Anke& Böhm, Christian. Measuring Non-Gaussianity by Phi-Transformed and Fuzzy Histograms. Advances in Artificial Neural Systems. 2012. Vol. 2012, no. 2012, pp.1-13.
https://search.emarefa.net/detail/BIM-511750
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-511750