RobustICA algorithm for independent component analysis

RobustICA is based on the normalized kurtosis contrast function, which is optimized by a computationally efficient iterative technique. This technique computes algebraically the step size (adaption coefficient) globally optimizing the contrast in the search direction at each iteration. Any independent component with non-zero kurtosis can be extracted in this manner.

The present implementation performs the deflationary separation of statistically independent sources under the instantaneous linear mixture model. Full separation is achieved if at most one source has zero kurtosis.

Some advantages of RobustICA are:

More details about the RobustICA algorithm and its comparative performance analysis can be found in references [1]-[3] below. A similar optimization technique is used in the OS-CMA.


Download the RobustICA package (Release 3, November 21, 2014; Matlab version; 27KB).
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