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

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DOI: 10.4236/jbise.2010.36083    4,068 Downloads   7,281 Views Citations

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.

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Khare, V. , Santhosh, J. , Anand, S. and Bhatia, M. (2010) Performance comparison of neural network training methods based on wavelet packet transform for classification of five mental tasks. Journal of Biomedical Science and Engineering, 3, 612-617. doi: 10.4236/jbise.2010.36083.

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