Performance comparison using five ANN methods for classification of EEG signals of two mental states

Author

Khare, Vijay ; Santhosh, Jayashree ; Anand, Sneh

Author_Institution

ECE Dept., JIIT Univ., Noida

Volume

1

fYear

2008

fDate

11-13 Dec. 2008

Firstpage

7

Lastpage

10

Abstract

The Paper demonstrate the comparison of performance by five artificial neural network (ANN) technique (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 for classification of planning of right hand movement with respect to an awake relaxed state. Wavelet packet transform (WPT) was used for Feature extraction of the relevant electroencephalogram (EEG) signals.

Keywords

electroencephalography; feature extraction; medical signal processing; signal classification; ANN methods; EEG signals; Levenberg-Marquardt; artificial neural network; awake relaxed state; conjugate learning gradient back propagation; feature extraction; gradient descent back propagation; mental states; performance comparison; resilient back propagation; right hand movement; signal classification; wavelet packet transform; Artificial neural networks; Biological neural networks; Electrodes; Electroencephalography; Eyes; Feature extraction; Frequency; Low pass filters; Wavelet packets; Wavelet transforms; Artificial Neural Network (ANN); BCI; Electroencephalogram (EEG); Rehabilitation; Wavelet Packet Transform (WPT);

fLanguage

English

Publisher

ieee

Conference_Titel

India Conference, 2008. INDICON 2008. Annual IEEE

Conference_Location

Kanpur

Print_ISBN

978-1-4244-3825-9

Electronic_ISBN

978-1-4244-2747-5

Type

conf

DOI

10.1109/INDCON.2008.4768792

Filename

4768792