Abstract
The main differences between the mixed signals and origin signals: Gaussian probability density function, statistical independence and temporal predictability. The proposed BSS algorithms mainly derived from the Gaussian probability density function and statistical independence. A new adaptive method is proposed in the paper. The method uses the temporal predictability as cost function which is not studied as much as other generic differences between the properties of signals and their mixtures. Step-adaptive nature gradient algorithm is proposed to separate signals, which is more robust and effective. Compared to fixed step natural gradient algorithm, Simulations show a good performance of the algorithm.
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© 2006 Springer-Verlag Berlin Heidelberg
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Tao, H., Zhang, Jy., Yu, L. (2006). A New Step-Adaptive Natural Gradient Algorithm for Blind Source Separation. In: Huang, DS., Li, K., Irwin, G.W. (eds) Intelligent Control and Automation. Lecture Notes in Control and Information Sciences, vol 344. Springer, Berlin, Heidelberg . https://doi.org/10.1007/978-3-540-37256-1_5
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DOI: https://doi.org/10.1007/978-3-540-37256-1_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37255-4
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