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Automatic epilepsy recognition with using HOS analysis of EEG signals
In this paper, a higher order spectra scheme is proposed for recognition of epilepsy states. Epilepsy is a brain disorder that is characterized by sudden and recurrent seizures. we known that higher order spectra contain ...
Performance Analysis of PSO and GA Algorithms in Order to Classifying EEG Data
In this Research, a new method has been proposed in order to classify the mental tasks
which represent the Electroencephalogram (EEG) signal as time series. Time series are kind
of data format which depict signal voltage varieties...
Coherence-based correntropy spectral density: A novel coherence measure for functional connectivity of EEG signals
network can be formed, which shows the relationship and the extent of dependency among the aforementioned time series. In order to evaluate the interdependency of EEG signals acquired from different electrodes, we proposed a new nonlinear connectivity...
Fast and robust Detection of Epilepsy in Noisy EEG Signals Using Permutation Entropy
Fast and robust Detection of Epilepsy in Noisy EEG Signals Using Permutation Entropy...
Higher Order Spectra Analysis of EEG Signals in Emotional Stress States
This paper proposes an emotional stress recognition system with EEG signals using higher order spectra (HOS). A visual induction based acquisition protocol is designed for recording the EEG signals in five channels (FP1, FP2, T3, T4 and Pz) under...