صورة الغلاف

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...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
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:
TK Electrical engineering. Electronics Nuclear engineering
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!

الانترنت

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

مواد مشابهة