Hybrid approach for classification of electroencephalographic signals using time–frequency images with wavelets and texture features
NJ Sairamya, L Susmitha, ST George… - Intelligent data analysis …, 2019 - Elsevier
Achieving the objective of identifying epileptic seizure activities automatically using
electroencephalographic (EEG) signals is of great significance in the treatment of epilepsy.
To realize this goal, a hybrid approach to analyze the time–frequency (t–f) image of EEG
signals is employed in this study. In the proposed approach, the EEG signals are
transformed into at–f image using short-time Fourier transform and the t–f images are further
decomposed into various component images by applying coiflet wavelet transformation. The …
electroencephalographic (EEG) signals is of great significance in the treatment of epilepsy.
To realize this goal, a hybrid approach to analyze the time–frequency (t–f) image of EEG
signals is employed in this study. In the proposed approach, the EEG signals are
transformed into at–f image using short-time Fourier transform and the t–f images are further
decomposed into various component images by applying coiflet wavelet transformation. The …
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