Brain Computer Interface Design Using Neural Network Classification of Autoregressive Models of Mental Task Electroencephalogram Signals.
Autoregressive(AR) feature extraction and neural network(NN) classification techniques are conducted using Electroencephalogram(EEG) signals extracted during mental tasks for Brain Computer Interface (BCI) design. The output of the BCI design could be used with a translation scheme such as Morse Cod...
محفوظ في:
المؤلف الرئيسي: | Huan, Nai Jen |
---|---|
التنسيق: | أطروحة |
منشور في: |
2004
|
الموضوعات: | |
الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
مواد مشابهة
-
Brain Computer Interface Design Using Neural Network Classification Of Autoregressive Models Of Mental Task Electroencephalogram Signals.
بواسطة: Huan , Nai Jen
منشور في: (2004) -
Kinetic gas molecule optimisation neural network for classification of electrocardiogram signals to identify heart disorder
بواسطة: Moein, Sara
منشور في: (2012) -
An Enhanced Probabilistic Neural Network For Pattern Classification
بواسطة: Chang, Roy Kwang Yang
منشور في: (2010) -
Grouping and deploying fine-grained tasks on grid by learning performance data
بواسطة: Muthuvelu, Nithiapidary
منشور في: (2011) -
The study of visual interface aesthetics in educational website Kansei engineering approach
بواسطة: Nur Faraha Hj. Mohd. Naim
منشور في: (2016)