Epileptic seizure detection by combining robust-principal component analysis and least square-support vector machine-Reference-Cited by-同舟云学术

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Epileptic seizure detection by combining robust-principal component analysis and least square-support vector machine

Published:2017-11-20 Issue:4 Volume:27 Page:368-375
ISSN:0899-9457
Container-title:International Journal of Imaging Systems and Technology
language:en
Short-container-title:Int. J. Imaging Syst. Technol.

Author:

Chen Shanen¹,Zhang Xi¹^ORCID,Yang Zhixian²

Affiliation:

1. Department of Industrial Engineering and Management; Peking University; Beijing China

2. Department of Pediatrics; Peking University First Hospital; Beijing China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Software,Electronic, Optical and Magnetic Materials

Reference24 articles.

1. Classification of focal and nonfocal EEG signals using ANFIS classifier for epilepsy detection;Deivasigamani;Int J Imaging Syst Technol.,2016

2. Feature extraction based on sparse representation with application to epileptic EEG classification;Wang;Int J Imaging Syst Technol.,2013

3. EEG-based brain source localization using visual stimuli;Jatoi;Int J Imaging Syst Technol.,2016

4. Real-time epileptic seizure prediction using AR models and support vector machines;Chisci;IEEE Trans Biomed Eng.,2010

5. Seizure prediction with spectral power of EEG using cost-sensitive support vector machines;Park;Epilepsia,2011

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1. EEG Epileptic Data Classification Using the Schrodinger Operator’s Spectrum;2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC);2023-07-24

2. Seizure detection algorithm based on multidimensional covariance matrix and binary Harris hawks optimization with Cauthy-Gaussian mutation;IEEE Sensors Journal;2023

3. Automatic Detection of Epilepsy Based on Entropy Feature Fusion and Convolutional Neural Network;Oxidative Medicine and Cellular Longevity;2022-05-11

4. A systematic mapping of feature extraction and feature selection methods of electroencephalogram signals for neurological diseases diagnostic assistance;IEEE Latin America Transactions;2021-05

5. Artifact cleaning of motor imagery EEG by statistical features extraction using wavelet families;International Journal of Circuit Theory and Applications;2020-08-09

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