ISNN 2004: Advances in Neural Networks – ISNN 2004 pp 702-707 | Cite as
A Novel Denoising Algorithm Based on Feedforward Multilayer Blind Separation
Abstract
The blind source separation algorithm always does its best to retrieve source signals, so in fact the output is generally a stronger source added by some other weaker sources and noises. The algorithm proposed in this paper assume the mixture of the weaker sources and noises as a new source Snew, and the outputs of last separation can be regard as the sources of next separation after proper choice and combination. Then Snew can be separated by using blind separation technique repeatedly. The spectrum difference between Snew and a selected restored source helps to eliminate the influence of noises and improve the performance of this method. What is more, similitude phase graph is also proposed in this paper, which can show the performance of blind separation algorithm straightly.
Keywords
Spectrum Difference Independent Component Analysis Mean Amplitude Blind Source Separation Denoising MethodPreview
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