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In this study, it was aimed that making epilepsy diagnosis by automatically evaluation of EEG records. Diagnosis system consists two steps which are feature extraction/selection and classification. Discrete wavelet transform (DWT) and artificial neural networks (ANN) were used to determine attribute vectors and classification, respectively. Classification accuracy was achieved as 99.62% by examining effects of varied wavelets on multi layer perceptron (MLP) networks which have different architecture and were trained different learning algorithms.