Automatic epilepsy detection using hybrid decomposition with multi class support vector method

摘要: The epilepsy has been detected from the electroencephalogram (EEG) by utilizing complex wavelet transform with support vector machine. These methods successfully examine each and every frequency in EEG signal for detecting effective manner because is one of most important brain abnormalities which affect entire function. occurring due to stroke, lack blood flow, fever so on, these lead create number human deaths. So, needs be analyzed it improving recognition rate. But major problem accuracy efficiency classifier traditional approximation entropy only extracts minimum features difficult detect manner. problems increase false classification rate while analyzing features. automatically recognized using various machine learning steps like preprocessing, decomposition, feature extraction, selection classification. In this research, Epilepsy applying Hybrid Multi Class Support Vector Machine (HMCSVM). Then performance system experimental results discussions.