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The identification of seizure activities in non-stationary electroencephalography (EEG) is a challenging task. The seizure detection by human inspection of EEG signals is prone to errors, inaccurate as well as time-consuming. Several attempts have been made to develop automatic systems so as to assist neurophysiologists in identifying epileptic seizures accurately. The proposed study brings forth...
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