Epileptic seizure detection based on the kernel extreme learning machine
Liu, Qi1; Zhao, Xiaoguang1; Hou, Zengguang1; Liu, Hongguang2
2017
发表期刊TECHNOLOGY AND HEALTH CARE
卷号25页码:S399-S409
文章类型Article
摘要This paper presents a pattern recognition model using multiple features and the kernel extreme learning machine (ELM), improving the accuracy of automatic epilepsy diagnosis. After simple preprocessing, temporal-and wavelet-based features are extracted from epileptic EEG signals. A combined kernel-function-based ELM approach is then proposed for feature classification. To further reduce the computation, Cholesky decomposition is introduced during the process of calculating the output weights. The experimental results show that the proposed method can achieve satisfactory accuracy with less computation time.
关键词Epileptic Eeg Multiple Features Elm Kernel Function Cholesky Decomposition
WOS标题词Science & Technology ; Life Sciences & Biomedicine ; Technology
DOI10.3233/THC-171343
关键词[WOS]SUPPORT VECTOR MACHINE ; FEATURE-EXTRACTION ; EEG SIGNALS ; ENTROPY ; CLASSIFICATION ; COEFFICIENTS
收录类别SCI ; ISTP
语种英语
WOS研究方向Health Care Sciences & Services ; Engineering
WOS类目Health Care Sciences & Services ; Engineering, Biomedical
WOS记录号WOS:000406157200044
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/20703
专题复杂系统管理与控制国家重点实验室_先进机器人
作者单位1.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Inst Automat, Beijing, Peoples R China
2.Chinese Peoples Publ Secur Univ, Inst Crime, Beijing, Peoples R China
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Liu, Qi,Zhao, Xiaoguang,Hou, Zengguang,et al. Epileptic seizure detection based on the kernel extreme learning machine[J]. TECHNOLOGY AND HEALTH CARE,2017,25:S399-S409.
APA Liu, Qi,Zhao, Xiaoguang,Hou, Zengguang,&Liu, Hongguang.(2017).Epileptic seizure detection based on the kernel extreme learning machine.TECHNOLOGY AND HEALTH CARE,25,S399-S409.
MLA Liu, Qi,et al."Epileptic seizure detection based on the kernel extreme learning machine".TECHNOLOGY AND HEALTH CARE 25(2017):S399-S409.
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