An automatic detection of focal EEG signals using new class of time–frequency localized orthogonal wavelet filter banks

作者：

Highlights：

• Proposed an automatic detection of focal and non-focal EEG signals.

• Design of a new class of time-frequency localized wavelet filter banks.

• Obtained the highest classification accuracy of 94.25%.

• Computationally faster than all existing methods.

摘要

•Proposed an automatic detection of focal and non-focal EEG signals.•Design of a new class of time-frequency localized wavelet filter banks.•Obtained the highest classification accuracy of 94.25%.•Computationally faster than all existing methods.

论文关键词：EEG,Epilepsy,Focal EEG signals,Non–focal EEG signals,Time–frequency localization,Wavelet filter banks,LS–SVM,Wavelet entropies

论文评审过程：Received 12 July 2016, Revised 22 November 2016, Accepted 27 November 2016, Available online 30 November 2016, Version of Record 12 January 2017.

论文官网地址：https://doi.org/10.1016/j.knosys.2016.11.024