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...
محفوظ في:
المؤلفون الرئيسيون: | Mohd Zaidi, Mohd Tumari, Asrul, Adam, Mohd Ibrahim, Shapiai, Mohd Saberi, Mohamad, Marizan, Mubin |
---|---|
التنسيق: | مقال |
اللغة: | English |
منشور في: |
Hindawi Publishing Corporation
2014
|
الموضوعات: | |
الوصول للمادة أونلاين: | 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 http://umpir.ump.edu.my/id/eprint/6465/ http://dx.doi.org/10.1155/2014/973063 |
الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
مواد مشابهة
-
Feature selection and classifier parameters estimation for EEG signals peak detection using particle swarm optimization
بواسطة: Adam, Asrul, وآخرون
منشور في: (2014) -
Feature Selection and Classifier Parameter Estimation for Egg Signal Peak Detection using Gravitational Search Algorithm
بواسطة: Zuwairie, Ibrahim, وآخرون
منشور في: (2014) -
Evaluation Of Different Peak Models Of Eye Blink Eeg For Signal Peak Detection Using Artificial Neural Network
بواسطة: Asrul, Adam, وآخرون
منشور في: (2016) -
Dingle's Model-based EEG Peak Detection using a Rule-based Classifier
بواسطة: Asrul, Adam, وآخرون
منشور في: (2015) -
Feature Selection using Angle Modulated Simulated Kalman Filter for Peak Classification of EEG Signals
بواسطة: Asrul, Adam, وآخرون
منشور في: (2016)