Epileptic EEG classification based on extreme learning machine and nonlinear features

Epilepsy Research

Volumn 96, Issue 1-2, 2011, Pages 29-38

  Yuan, Qi ^a   Zhou, Weidong ^a   Li, Shufang ^a   Cai, Dongmei ^a  

^a SHANDONG UNIVERSITY   (China)

Author keywords

Approximate entropy (ApEn); Detrended fluctuation analysis (DFA); Epileptic EEG; Extreme learning machine (ELM); Hurst exponent; Support vector machine (SVM)

Indexed keywords

ACCURACY; ALGORITHM; ANALYTICAL PARAMETERS; ARTICLE; ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION; CONTROLLED STUDY; DETRENDED FLUCTUATION ANALYSIS; DISEASE CLASSIFICATION; ELECTROENCEPHALOGRAM; ENTROPY; EPILEPSY; EXTREME LEARNING MACHINE; HURST EXPONENT; MACHINE LEARNING; NONLINEAR SYSTEM; PRIORITY JOURNAL; SATISFACTION; SCALING EXPONENT; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING; SINGLE HIDDEN LAYER FEEDFORWARD NEURAL NETWORK; SUPPORT VECTOR MACHINE;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; ELECTROENCEPHALOGRAPHY; ENTROPY; EPILEPSY; FEMALE; HUMANS; MALE; NEURAL NETWORKS (COMPUTER); NONLINEAR DYNAMICS; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 80052836687     PISSN: 09201211     EISSN: 18726844     Source Type: Journal    
DOI: 10.1016/j.eplepsyres.2011.04.013     Document Type: Article

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