Pramanick, Puloma (2013) Classification of electroencephalogram (EEG) signal based on fourier transform and neural network. BTech thesis.
Human normal and epileptic electroencephalogram (EEG) signals have been analysed using Fourier Transform (FT). The area under the spectrum of both normal and epileptic EEG is calculated as feature for classification. The classification is done with the help of neural network (Levenberg - Marquardt algorithm).Our final goal of the study is the automatic detection of the epileptic disorders in the EEG in order to support the diagnosis and care of the epileptic syndromes and related seizure disorders.
|Item Type:||Thesis (BTech)|
|Uncontrolled Keywords:||spectrum; EEG signal; neural network|
|Subjects:||Engineering and Technology > Electrical Engineering > Power Networks|
|Divisions:||Engineering and Technology > Department of Electrical Engineering|
|Deposited By:||Hemanta Biswal|
|Deposited On:||31 Oct 2013 09:29|
|Last Modified:||20 Dec 2013 14:00|
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