MODELING BRAIN WAVE DATA BY USING ARTIFICIAL NEURAL NETWORKS

Year 2010, Volume: 39 Issue: 1, 81 - 88, 03.07.2019

Çağdaş Hakan Aladağ , Erol Eğrioğlu , Cem Kadılar

Abstract

Artificial neural networks can successfully model time series in real life.
Because of their success, they have been widely used in various fields of
application. In this paper, artificial neural networks are used to model
brain wave data which has been recorded during the Wisconsin Card
Sorting Test. The forecasting performances of different artificial neural
network models, such as feed forward and recurrent neural networks,
using both linear and nonlinear activation functions in the output neuron, are examined. As a result of the analysis, it is found that artificial
neural networks model the data successfully and all the models employed produce very accurate forecasts.

Keywords

Activation function, Brain wave data, Elman recurrent neural networks, Feed forward neural networks, Forecasting, Wisconsin card sorting test

References

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