Electroencephalogram (EEG) is one the most common tools for epilepsy diagnosis and analysis‎. Currently, epilepsy diagnosis is still mainly performed by a neurologist through manual or visual inspection of EEG signals‎. In this article, we develop a computer aided diagnosis (CAD) for epilepsy based on discrete wavelet transform (DWT), Shannon entropy ‎and feed-forward neural network (FFNN). ‎DWT decompose ‎EEG signals into several frequency sub-bands such as delta, theta, ‎alpha, beta and gamma. Shannon entropy extract the EEG features from each these frequency sub-bands.