Adaptive-Geometric methods: application to the separation of EEG signals
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چکیده
This paper presents a new adaptive algorithm for the online linear and non-linear separation of signals with nonuniform, symmetrical probability distributions. The procedure is based on the interpretation and properties of the vectorial spaces of sources and mixtures, using a multiple linearization in the mixture space. The main characteristics of the procedure are its simplicity, its immunity to symmetrically-distributed additive noise, and the rapid convergence experimentally validated when the method is applied to the separation of multiple EEG signals.
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تاریخ انتشار 2004