摘要：The inception of learning was through neural networks. ANN has ushered into many fields providing solutions for critical solutions, particular in medical and health care systems. Brain neurological disorder is epilepsy; electroencephalograph is the tool to study it. EEG recordings consume lot of time and they are with uncertain frequencies. Only experts can study and diagnose epilepsy perfectly, even uncertainty rules over into ambiguities. Deep Learning has solutions to solve on the data with multivariate, temporal, uncertainty in nature. EEGs are obtained as signal data as frequency graphs from the electroencephalography devices, digitized into images. Feature extraction and classification is the most challenging on EEG signal datasets. In this paper, a survey on EEG data sets, analyses method and contributions of CNN in EEG signal data analysis have been discussed, to provide direction for the researchers to handle the most challenging problems.
