Performance comparison of neural network training methods based on wavelet packet transform for classification of five mental tasks

Vijay Khare, Jayashree Santhosh, Sneh Anand, Manvir Bhatia

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DOI: 10.4236/jbise.2010.36083                

Abstract

In this study, performances comparison to discriminate five mental states of five artificial neural network (ANN) training methods were investigated. Wavelet Packet Transform (WPT) was used for feature extraction of the relevant frequency bands from raw electroencephalogram (EEG) signals. The five ANN training methods used were (a) Gradient Descent Back Propagation (b) Levenberg-Marquardt (c) Resilient Back Propagation (d) Conjugate Learning Gradient Back Propagation and (e) Gradient Descent Back Propagation with movementum.

Keywords

Electroencephalogram (EEG); Wavelet Packet Transform (WPT); Artificial Neural Network (ANN)

Conflicts of Interest

The authors declare no conflicts of interest.

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