LU triangularization extreme learning machine in EEG cognitive task classification

• Published in: Neural computing & applications Vol. 31; no. 4; pp. 1117 - 1126
• Main Authors: Kutlu, Yakup, Yayık, Apdullah, Yildirim, Esen, Yildirim, Serdar
• Format: Journal Article
• Language: English
• Published: London Springer London 01.04.2019; Springer Nature B.V
• Subjects: Arithmetic; Artificial Intelligence; Brain; Classification; Classifiers; Cognition & reasoning; Cognitive tasks; Computational Biology/Bioinformatics; Computational Science and Engineering; Computer Science; Data Mining and Knowledge Discovery; Electroencephalography; Image Processing and Computer Vision; Neural networks; Original Article; Probability and Statistics in Computer Science; Signal processing; Singular value decomposition; Optimized nodes; MoDP method; Cognitive processes; Extreme learning machine; Lower–upper triangularization

Electroencephalography (EEG) has been used as a promising tool for investigation of brain activity during cognitive processes. The aim of this study is to reveal whether EEG signals can be used for classifying cognitive processes: arithmetic tasks and text reading. A recently introduced EEG database...