Improved techniques for independent component analysis

The traditional independent component analysis (ICA) approach aims to separate all underlying independent components (original sources) from their mixtures simultaneously. Through introducing specific prior information about a source signal, an improved ICA algorithm is derived in this paper. One can extract a desired source signal while its normalized kurtosis range is known in advance. The utility of the proposed algorithm is demonstrated by computer simulations on biomedical signals.