An incremental framework for classification of EEG signals using quantum particle swarm optimization
作者： Kaveh Hassani , Won-Sook Lee
DOI: 10.1109/CIVEMSA.2014.6841436
关键词:
摘要: Classification of electroencephalographic (EEG) signals is a sophisticated task that determines the accuracy thought pattern recognition performed by computer-brain interface (BCI) which, in turn, degree naturalness interaction provided system. However, classifying EEG not trivial due to their non-stationary characteristics. In this paper, we introduce and utilize incremental quantum particle swarm optimization (IQPSO) algorithm for classification data stream. IQPSO builds model as set explicit rules which benefits from semantic symbolic knowledge representation enhanced comprehensibility. We compared performance against ten other classifiers on two datasets. The results suggest outperforms terms accuracy, precision recall.
sci-hub.se 参考文章(40)
Yanbin Ge, Yan Wu, Towards adaptive classification of motor imagery EEG using biomimetic pattern recognition international conference on intelligent computing. pp. 455- 460 ,(2011) , 10.1007/978-3-642-25944-9_59
L. F. Nicolas-Alonso, R. Corralejo, D. Álvarez, R. Hornero, Adaptive Classification Framework for Multiclass Motor Imagery-Based BCI Springer, Cham. pp. 762- 765 ,(2014) , 10.1007/978-3-319-00846-2_189
C. R. Hema, M. P. Paulraj, S. Yaacob, A. H. Adom, R. Nagarajan, Particle Swarm Optimization Neural Network based Classification of Mental Tasks Springer, Berlin, Heidelberg. pp. 883- 888 ,(2008) , 10.1007/978-3-540-69139-6_218
Xiaoming Zheng, Banghua Yang, Xiang Li, Peng Zan, Zheng Dong, Classifying EEG using incremental support vector machine in BCIs international conference on intelligent computing for sustainable energy and environment. pp. 604- 610 ,(2010) , 10.1007/978-3-642-15615-1_71
Alex A. Freitas, A survey of evolutionary algorithms for data mining and knowledge discovery Advances in evolutionary computing. pp. 819- 845 ,(2003) , 10.1007/978-3-642-18965-4_33
Jun Sun, Bin Feng, Wenbo Xu, Particle swarm optimization with particles having quantum behavior congress on evolutionary computation. ,vol. 1, pp. 325- 331 ,(2004) , 10.1109/CEC.2004.1330875
M. F. Mohamed Saaid, W. A. B. Wan Abas, H. Aroff, N. Mokhtar, R. Ramli, Z. Ibrahim, Change Point Detection of EEG Signals Based on Particle Swarm Optimization IFMBE Proceedings. pp. 484- 487 ,(2011) , 10.1007/978-3-642-21729-6_122
Muhammad Bilal Khalid, Naveed Iqbal Rao, Intisar Rizwan-i-Haque, Sarmad Munir, Farhan Tahir, Towards a Brain Computer Interface using wavelet transform with averaged and time segmented adapted wavelets international conference on computer, control and communication. pp. 1- 4 ,(2009) , 10.1109/IC4.2009.4909189
Qing Guo Wei, Yan Mei Wang, Zong Wu Lu, Cultural-Based Multi-Objective Particle Swarm Optimization for EEG Channel Reduction in Multi-Class Brain-Computer Interfaces Applied Mechanics and Materials. pp. 1027- 1032 ,(2012) , 10.4028/WWW.SCIENTIFIC.NET/AMM.239-240.1027
Gözde Bakırlı, Derya Birant, Alp Kut, An incremental genetic algorithm for classification and sensitivity analysis of its parameters Expert Systems With Applications. ,vol. 38, pp. 2609- 2620 ,(2011) , 10.1016/J.ESWA.2010.08.051