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On-Line Arithmetic Based Reprogrammable Hardware Implementation of LVQ Neural Network for Alertness Classification


Mohamed Boubaker, Khaled Ben Khalifa, Bernard Girau, Mohamed Dogui, Mohamed H?di Bedoui


Vol. 8  No. 3  pp. 260-266


The current study presents the hard implementation of a learning Vector Quantization (LVQ) neural network. Starting from the spectral EEG analysis, we suggest an LVQ serial on-line architecture implementation on a Field programmable Gate Array (FPGA) circuit. Our concern was mainly to get a light, easy-to-wear system for the classification of vigilance levels in humans using EEG signals. The results of these classified states by LVQ mode are presented in this paper. Furthermore, the highly-satisfactory performances of our implementation in terms of area speed and delay are described.


LVQ neural network, on-line arithmetics, FPGA, EEG and vigilance