Efficient classification using multiple mental thoughts.

A. Zafar; M. I. Ahmad; A. Hanif

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Efficient classification using multiple mental thoughts.

Author(s)

A. Zafar Department of Electrical Engineering, Wah Engineering College, University of Wah, Wah Cantt, Pakistan

M. I. Ahmad Department of Electrical Engineering, Wah Engineering College, University of Wah, Wah Cantt, Pakistan

A. Hanif Department of Electrical Engineering, Wah Engineering College, University of Wah, Wah Cantt, Pakistan

Abstract

Researches in personal identification show that classification using multiple mental thoughts increases complexity and system’s processing time. In this paper, an efficient classification algorithm is proposed to classify an individual using multiple mental thoughts. Features from Electroencephalography (EEG), used as biometric, are extracted using sixth order Autoregressive (AR) model, and Linear Discriminant Analysis (LDA) based classification is performed based on best mental thought combinations. Matlab® simulation results indicate that the proposed algorithm reduces the complexity as well as the processing time that confirms the use of EEG as a biometric for personal identification.

Publication Details

Page(s) 45-51

DOI DOI not available

Published Journal: Nucleus, Volume: 50, Issue: 1, Year: 2013

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