Abstract
Epilepsy is a chronic recurrent transient brain dysfunction syndrome. It is characterized by recurrent epilepsy caused by abnormal discharge of brain neurons. Epilepsy is one of the common diseases in nervous system. The analysis of EEG signals is a hot topic in current research. In order to solve the problem of epileptic EEG signals classification accurately, we carry out in-depth research on epileptic EEG signals, analyze features from linear and non-linear perspectives, input them into the improved RBF model to dynamically extract effective features, and introduce one against one strategy classifier to reduce the probability of error classification. Experiments show that the proposed algorithm has strong robustness and high epileptic signal recognition rate.
Highlights
Epilepsy is a transient brain dysfunction caused by sudden abnormal over discharge of brain neurons, which has a high incidence rate (Jiang et al, 2020)
The method of multi-feature extraction and intelligent recognition has been applied to the recognition of epileptic EEG signals (Ojha et al, 2020)
Guo et al (2010) realizes EEG signal classification based on intelligent network
Summary
Epilepsy is a transient brain dysfunction caused by sudden abnormal over discharge of brain neurons, which has a high incidence rate (Jiang et al, 2020). The method of multi-feature extraction and intelligent recognition has been applied to the recognition of epileptic EEG signals (Ojha et al, 2020). Guo et al (2010) realizes EEG signal classification based on intelligent network.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
