EEG Signal Classification with Different Signal Representations
نویسندگان
چکیده
If several mental states can be reliably distinguished by recognizing patterns in EEG, then a paralyzed person could communicate to a device like a wheelchair by composing sequencesof these mental states. In this article, we report on a study comparing four representations of EEG signals and their classification by a two-layer neural network with sigmoid activation functions. The neuralnetwork is implemented on a CNAPS server (128 processor, SIMD architecture) by Adaptive Solutions, Inc., gaining a 100-fold decrease in training time over a Sun Sparc 10 for a large number of hidden units.
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تاریخ انتشار 1995