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GECCO
1999
Springer

Forecasting the MagnetoEncephaloGram (MEG) of Epileptic Patients Using Genetically Optimized Neural Networks

9 years 5 months ago
Forecasting the MagnetoEncephaloGram (MEG) of Epileptic Patients Using Genetically Optimized Neural Networks
In this work MagnetoEncephaloGram (MEG) recordings of epileptic patients were analyzed using a hybrid neural networks training algorithm. This algorithm combines genetic algorithms and a training method based on the localized Extended Kalman Filter (EKF), in order to evolve the structure and train Multi-Layered Perceptrons (MLP) networks. Our goal is to examine the predictability of the MEG signal on a short and long predicting horizon. Numerous experiments were conducted giving highly successful results.
Adam V. Adamopoulos, Efstratios F. Georgopoulos, S
Added 04 Aug 2010
Updated 04 Aug 2010
Type Conference
Year 1999
Where GECCO
Authors Adam V. Adamopoulos, Efstratios F. Georgopoulos, Spiridon D. Likothanassis, Photios A. Anninos
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