caa a22 4500 606160299 CHVBK 20210128100629.0 cr unu---uuuuu 210128e20150701xx s 000 0 eng 10.1007/s00521-014-1786-7 doi (NATIONALLICENCE)springer-10.1007/s00521-014-1786-7 Comparison of classification methods on EEG signals based on wavelet packet decomposition [Elektronische Daten] [Yong Zhang, Yuting Zhang, Jianying Wang, Xiaowei Zheng] EEG signals play an important role in both the diagnosis of neurological diseases and understanding the psychophysiological processes. Classification of EEG signals includes feature extraction and feature classification. This paper uses approximate entropy and sample entropy based on wavelet package decomposition as the feature exaction methods and employs support vector machine and extreme learning machine as the classifiers. Experiments are performed in epileptic EEG data and five mental tasks, respectively. Experimental results show that the combination strategy of sample entropy and extreme learning machine has shown great performance, which obtains good classification accuracy and low training time. The Natural Computing Applications Forum, 2014 EEG nationallicence Wavelet packet nationallicence Classification nationallicence Approximate entropy nationallicence Extreme learning machine nationallicence Zhang Yong School of Computer and Information Technology, Liaoning Normal University, No. 1, Liushu South Street, Ganjingzi District, 116081, Dalian, Liaoning Province, China aut Zhang Yuting School of Computer and Information Technology, Liaoning Normal University, No. 1, Liushu South Street, Ganjingzi District, 116081, Dalian, Liaoning Province, China aut Wang Jianying School of Psychology, Liaoning Normal University, 116029, Dalian, China aut Zheng Xiaowei School of Computer and Information Technology, Liaoning Normal University, No. 1, Liushu South Street, Ganjingzi District, 116081, Dalian, Liaoning Province, China aut Neural Computing and Applications Springer London 26/5(2015-07-01), 1217-1225 0941-0643 26:5<1217 2015 26 521 https://doi.org/10.1007/s00521-014-1786-7 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00521-014-1786-7 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Zhang Yong School of Computer and Information Technology, Liaoning Normal University, No. 1, Liushu South Street, Ganjingzi District, 116081, Dalian, Liaoning Province, China aut NATIONALLICENCE 700 1- Zhang Yuting School of Computer and Information Technology, Liaoning Normal University, No. 1, Liushu South Street, Ganjingzi District, 116081, Dalian, Liaoning Province, China aut NATIONALLICENCE 700 1- Wang Jianying School of Psychology, Liaoning Normal University, 116029, Dalian, China aut NATIONALLICENCE 700 1- Zheng Xiaowei School of Computer and Information Technology, Liaoning Normal University, No. 1, Liushu South Street, Ganjingzi District, 116081, Dalian, Liaoning Province, China aut NATIONALLICENCE 773 0- Neural Computing and Applications Springer London 26/5(2015-07-01), 1217-1225 0941-0643 26:5<1217 2015 26 521