An independent component analysis(ICA) algorithm based on the combination of negentropy and signal noise
ratio(SNR) is presented to solve the deficiency of traditional ICA method after the introduction of principle and algorithm of
ICA. The main formulas in the algorithm are elaborated and the idiographic steps of algorithm are given. Then the computer
simulation is used to testify the performance of this algorithm. Both the traditional fast ICA algorithm and the presented
ICA algorithm are applied to separate the mixed signal data. Experiment results show that the proposed method has better
performance on separating signals than the traditional fast ICA algorithm based on negentropy, and can estimate the source
signals from the mixed signals more exactly.