Classification of EEG signals for epileptic seizures using Levenberg-Marquardt algorithm based Multilayer Perceptron Neural Network

EEG is the most effective diagnostic technique to determine epilepsy in a patient. The objective of this research work is to apply classification techniques on EEG signals to determine whether the patient has suffered from epileptic seizure. This is carried out through the extraction of various time and frequency domain features. The two classifiers, i.e. Artificial Neural Network (ANN) and Support Vector Machine (SVM) are used and compared using various evaluation parameters. The simulation results and corresponding quantitative analysis shows that ANN classifier is superior to SVM.