Independent Component Analysis
Independent component analysis
Blind source separation
Probability density function
Cumulative distribution function
- EEG Signal
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.
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...
- Stone JV (2004) Independent component analysis: a tutorial introduction. MIT, BostonGoogle Scholar