Glossary
- ICA:
-
Independent component analysis
- BSS:
-
Blind source separation
- pdf:
-
Probability density function
- cdf:
-
Cumulative distribution function
- EEG Signal:
-
Electroencephalogram signal
Definition
Independent component analysis (ICA) (Hyvarinen et al. 2001; Stone 2004) extracts statistically independent variables from a set of measured variables, where each measured variable is affected by a number of underlying physical causes. Extracting such variables is desirable because independent variables are usually generated by different physical processes. Thus, by extracting independent variables, ICA can effectively extract the underlying physical causes for a given set of measured variables.
Introduction
Most measured quantities are actually mixtures of other quantities. Typical examples are: (a) sound signals in a room with several speakers; (b) an electroencephalogram (EEG) signal, which contains contributions from many...
This is a preview of subscription content, log in via an institution to check access.
References
Bell AJ, Sejnowski TJ (1995) An information-maximization approach to blind separation and blind deconvolution. Neural Comput 7:1129–1159
Bell AJ, Sejnowski TJ (1997) The independent components of natural scenes are edge filters. Vis Res 37(23):3327–3338
Hyvarinen A, Karhunen J, Oja E (2001) Independent component analysis. Wiley, New York
Makeig S, Jung T, Bell AJ, Ghahremani D, Sejnowski TJ (1997) Blind separation of auditory event-related brain responses into independent components. Proc Natl Acad Sci U S A 94:10979–10984
McKeown MJ, Makeig S, Brown GG, Jung TP, Kindermann SS, Sejnowski TJ (1998) Spatially independent activity patterns in functional magnetic resonance imaging data during the stroop color-naming task. Proc Natl Acad Sci U S A 95:803–810
Stone JV (2004) Independent component analysis: a tutorial introduction. MIT, Boston
Van Hateren JH, Van der Schaaf A (1998) Independent component filters of natural images compared with simple cells in primary visual cortex. Proc R Soc Lond B Biol Sci 265(7):359–366
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Section Editor information
Rights and permissions
Copyright information
© 2016 Springer Science+Business Media LLC
About this entry
Cite this entry
Efimov, D. (2016). Independent Component Analysis. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7163-9_147-1
Download citation
DOI: https://doi.org/10.1007/978-1-4614-7163-9_147-1
Received:
Accepted:
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-7163-9
Online ISBN: 978-1-4614-7163-9
eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering