Unique ICA solution by eliminating indeterminacy

Presents a method to eliminate inherent indeterminacy of permutation and dilation existing in the classical independent component analysis (ICA) by incorporating new constraints into the contrast function. We illustrate how this approach sorts independent components (ICs) in the order of significance according to some statistic and normalizes the demixing matrix or the energies of separated ICs automatically. With some prior information, the algorithm is able to identify and extract the original sources perfectly from their mixtures. The experiments with synthetic signals and audio signals demonstrate the efficacy and usage of eliminating indeterminacy in the ICA