EEG signals analysis : an application of wavelet transform techniques

Chen, Jean Zhu (1994). EEG signals analysis : an application of wavelet transform techniques M.Sc Thesis, School of Computer Science and Electrical Engineering, The University of Queensland.

       
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Author Chen, Jean Zhu
Thesis Title EEG signals analysis : an application of wavelet transform techniques
School, Centre or Institute School of Computer Science and Electrical Engineering
Institution The University of Queensland
Publication date 1994
Thesis type M.Sc Thesis
Supervisor Prof Ah Chung T soi
Total pages 111
Language eng
Subjects 09 Engineering
Formatted abstract

The project reported in this thesis aims to develop a computer analysis of electroencephalogram (EEG) signals in order to establish how particular EEG signals are to be classified as normal, obsessive compulsive disorder (OCD), or schizophrenic. We will present the results of the computation of wavelet transform of EEG signals, and the application of an artificial neural network (ANN), viz., multi-layer perceptron (MLP), for classification purposes. The findings of this project demonstrate that wavelet transform provides a viable approach to EEG signal analysis, and that ANN techniques prove to be a useful tool for their classifications. 

Keyword Electroencephalography -- Data processing
Signal processing -- Digital techniques

Document type: Thesis
Collection: UQ Theses (non-RHD) - UQ staff and students only
 
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Created: Fri, 09 Nov 2012, 12:09:46 EST by Eric Sun on behalf of Social Sciences and Humanities Library Service