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Myanmar Institute of Information Technology
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Sagaing University of Education
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Taunggyi University
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Technological University, Hmawbi
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Technological University (Kyaukse)
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University of Computer Studies, Mandalay
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University of Computer Studies, Taungoo
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University of Computer Studies, Yangon
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University of Dental Medicine Mandalay
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University of Dental Medicine, Yangon
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University of Information Technology
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Yangon University of Education
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New Index
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Item
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Analysis of Matching Pursuit Features of EEG Signal for Mental Tasks Classification
http://hdl.handle.net/20.500.12678/0000004410
http://hdl.handle.net/20.500.12678/0000004410a6ddcc38-2dbb-4340-8839-a6195f81780a
f13f2fd2-4ae8-4be2-a011-ee621a75458f
Name / File | License | Actions |
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Analysis of Matching Pursuit Features of EEG Signal.pdf (808 Kb)
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Publication type | ||||||
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Article | ||||||
Upload type | ||||||
Publication | ||||||
Title | ||||||
Title | Analysis of Matching Pursuit Features of EEG Signal for Mental Tasks Classification | |||||
Language | en_US | |||||
Publication date | 2015-02-05 | |||||
Authors | ||||||
Lwin, Zin Mar | ||||||
Thaw, Mie Mie | ||||||
Description | ||||||
Brain Computer Interface (BCI) Systems havedeveloped for new way of communication betweencomputer and human who are suffer from severe motordisabilities and difficult to communicate with theirenvironment. BCI let them for communication by nonmuscular way. For communication between human andcomputer, BCI uses a type of signal calledElectroencephalogram (EEG) signal which arerecorded from the human‘s brain by mean of electrode.Electroencephalogram (EEG) signal is an importantinformation source for knowing brain processes for thenon-invasive BCI. In translating human’s thought, itneeds to classify acquired EEG signal accurately.Independent Component analysis (ICA) method viaEEGLab Tools for removing artifacts which are causedby eye blinks in the recorded mental task EEG signal.For features extraction, the Time and Frequencyfeatures of non stationary EEG signals are extractedby Matching Pursuit (MP) algorithm. Theclassification of mental tasks is performed byMulti_Class Support Vector Machine (SVM). | ||||||
Keywords | ||||||
BCI, EEG, ICA, SVM | ||||||
Identifier | http://onlineresource.ucsy.edu.mm/handle/123456789/2344 | |||||
Journal articles | ||||||
Thirteenth International Conference On Computer Applications (ICCA 2015) | ||||||
Conference papers | ||||||
Books/reports/chapters | ||||||
Thesis/dissertations |