A blind source separation algorithm based on negentropy and signal noise ratio |
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| Authors: | WAN Jun ZHANG Xiao-hui RAO Jiong-hui and HU Qing-ping |
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| Institution: | Department of Weapon Engineering, Naval University of Engineering, Wuhan 430033, P. R. China |
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| Abstract: | A novel blind source separation (BSS) algorithm based on the combination of negentropy and signal noise ratio (SNR) is presented to solve the deficiency of the traditional independent component analysis (ICA) algorithm after the introduction of the principle and algorithm of ICA. The main formulas in the novel algorithm are elaborated and the idiographic steps of the algorithm are given. Then the computer simulation is used to test the performance of this algorithm. Both the traditional FastICA algorithm and the novel ICA algorithm are applied to separate mixed signal data. Experiment results show the novel method has a better performance in separating signals than the traditional FastICA algorithm based on negentropy. The novel algorithm could estimate the source signals from the mixed signals more precisely. |
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| Keywords: | blind source separation independent component analysis negentropy signal noise ratio |
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