EEG signals classification using the K-means clustering and a multilayer perceptron neural network model.
Umut OrhanMahmut HekimMahmut OzerPublished in: Expert Syst. Appl. (2011)
Keyphrases
- neural network model
- multilayer perceptron
- eeg signals
- input vectors
- neural network
- artificial neural networks
- multi layer perceptron
- probabilistic neural networks
- brain computer interface
- motor imagery
- input vector
- radial basis function neural network
- input variables
- signal processing
- network architecture
- back propagation
- hidden layer
- bp neural network
- rbf neural network
- activation function
- machine learning
- classification accuracy
- pattern recognition
- radial basis function
- support vector machine svm
- pattern classification
- rough sets
- eeg data
- support vector
- kernel density estimators
- brain signals
- electrical activity
- artificial intelligence
- decision trees
- feature extraction
- brain activity
- feedforward neural networks
- k means
- text classification