Accurate Classification of EEG Signals Using Neural Networks Trained by Hybrid Population-physic-based Algorithm

A brain-computer interface (BCI) system is one of the most effective ways that translates brain signals into output commands. Different imagery activities can be classified based on the changes in μ and β rhythms and their spatial distributions. Multi-layer perceptron neural networks (MLP-NNs) are c...

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Veröffentlicht in:	Machine intelligence research (Print) Jg. 17; H. 1; S. 108 - 122
Hauptverfasser:	Afrakhteh, Sajjad, Mosavi, Mohammad-Reza, Khishe, Mohammad, Ayatollahi, Ahmad
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Beijing Springer Nature B.V 01.02.2020
Schlagworte:	Algorithms Classification Convergence Electroencephalography Heuristic methods Human-computer interface Multilayer perceptrons Multilayers Neural networks Particle swarm optimization Recursive methods Search algorithms Signal classification Spatial distribution Training
ISSN:	2153-182X, 2153-1838
Online-Zugang:	Volltext
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