Feature Selection and Classifier Parameters Estimation for EEG Signals Peak Detection Using Particle Swarm Optimization
Electroencephalogram (EEG) signal peak detection is widely used in clinical applications. The peak point can be detected using several approaches, including time, frequency, time-frequency, and nonlinear domains depending on various peak features from several models. However, there is no study that...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi Publishing Corporation
2014
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/6465/ http://umpir.ump.edu.my/id/eprint/6465/ http://umpir.ump.edu.my/id/eprint/6465/ http://umpir.ump.edu.my/id/eprint/6465/1/Feature_Selection_and_Classifier_Parameters_Estimation_for_EEG_Signals_Peak_Detection_Using_Particle_Swarm_Optimization.pdf |