Genetic algorithm applied to ICA feature selection

In conventional feature extraction based on independent component analysis (ICA), feature selection and dimensional reduction are carried out only through PCA preprocessing, so the importance of independent components is not taken into consideration. In order to overcome this problem, a new ICA feature selection based on genetic algorithm is proposed in this paper. To demonstrate its effectiveness, recognition experiments is performed for face recognition and iris recognition.