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Novel images extraction model using improved delay vector variance feature extraction and multi-kernel neural network for EEG detection and prediction

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成果类型:
期刊论文、会议论文
作者:
Ge, Jing*;Zhang, Guoping(张国平
通讯作者:
Ge, Jing
作者机构:
[Zhang, Guoping; Ge, Jing] Cent China Normal Univ, Coll Phys Sci & Technol, Wuhan 430069, Hubei, Peoples R China.
通讯机构:
[Ge, Jing] C
Cent China Normal Univ, Coll Phys Sci & Technol, Wuhan 430069, Hubei, Peoples R China.
语种:
英文
关键词:
Bioimage processing;epileptic seizures detection;nonlinearity;neural network
期刊:
TECHNOLOGY AND HEALTH CARE
ISSN:
0928-7329
年:
2015
卷:
23
期:
S1
页码:
S151-S155
会议名称:
International Conference on Human Health and Medical Engineering (HHME)
会议时间:
DEC 07, 2014
会议地点:
Wuhan, PEOPLES R CHINA
会议主办单位:
[Ge, Jing;Zhang, Guoping] Cent China Normal Univ, Coll Phys Sci & Technol, Wuhan 430069, Hubei, Peoples R China.
会议赞助商:
Informat Technol & Ind Engn Res Ctr
出版地:
NIEUWE HEMWEG 6B, 1013 BG AMSTERDAM, NETHERLANDS
出版者:
IOS PRESS
机构署名:
本校为第一且通讯机构
院系归属:
物理科学与技术学院
摘要:
BACKGROUND: Advanced intelligent methodologies could help detect and predict diseases from the EEG signals in cases the manual analysis is inefficient available, for instance, the epileptic seizures detection and prediction. This is because the diversity and the evolution of the epileptic seizures make it very difficult in detecting and identifying the undergoing disease. Fortunately, the determinism and nonlinearity in a time series could characterize the state changes. Literature review indicates that the Delay Vector Variance (DVV) could exa...

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