Detection and classification of epileptic EEG signals by the methods of nonlinear dynamics-Reference-Cited by-同舟云学术

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Detection and classification of epileptic EEG signals by the methods of nonlinear dynamics

Published:2021-10 Issue: Volume:151 Page:111032
ISSN:0960-0779
Container-title:Chaos, Solitons & Fractals
language:en
Short-container-title:Chaos, Solitons & Fractals

Author:

Lu XiaoJie,Zhang JiQian,Huang ShouFang,Lu Jun,Ye MingQuan,Wang MaoSheng

Publisher

Elsevier BV

Subject

General Mathematics,General Physics and Astronomy,Statistical and Nonlinear Physics,Applied Mathematics

Reference34 articles.

1. Analysis of electrocorticogram in epilepsy patients in terms of criticality;Yan;Nonlinear Dyn,2016

2. Application of non-linear and wavelet based features for the automated identification of epileptic EEG signals;Acharya;Int J Neural Syst,2012

3. Classification of seizure based on the time-frequency image of EEG signals using HHT and SVM;Fu;Biomed Signal Process Control,2014

4. A new approach to characterize epileptic seizures using analytic time-frequency flexible wavelet transform and fractal dimension;Sharma;Pattern Recognit Lett,2017

5. Automatic EEG seizure detection using dual-tree complex wavelet-Fourier features;Chen;Expert Syst Appl,2014

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1. Decoding compositional complexity: Identifying composers using a model fusion-based approach with nonlinear signal processing and chaotic dynamics;Chaos, Solitons & Fractals;2024-10

2. Nonlinear analysis and recognition of epileptic EEG signals in different stages;Journal of Neurophysiology;2024-09-01

3. A novel multi-feature fusion attention neural network for the recognition of epileptic EEG signals;Frontiers in Computational Neuroscience;2024-06-19

4. Epileptic seizure prediction based on EEG using pseudo-three-dimensional CNN;Frontiers in Neuroinformatics;2024-03-19

5. Automatic classification of seizure and seizure-free EEG signals based on phase space reconstruction features;Journal of Biological Physics;2024-03-11

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