A study of recent classification algorithms and a novel approach for EEG data classification
作者： Eyup Cinar , Ferat Sahin
DOI: 10.1109/ICSMC.2010.5642424
关键词:
摘要: This paper analyzes the application of different classification techniques for Electroencephalography (EEG) signals. Fuzzy Functions Support Vector Classifier (FFSVC), Improved (IFFSVC) and a novel hybrid technique that has been designed utilizing Particle Swarm Optimization Radial Basis Function Networks (PSO-RBFN) have studied. The performance is compared on same standard datasets are publicly available used by many Brain Computer Interface (BCI) researchers. Results show proposed classifiers might reach state art be as alternative in applications EEG
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