The upper bound of the minimal number of hidden neurons for the parity problem in binary neural networks.
Yang LuJuan YangQiang WangZhenJin HuangPublished in: Sci. China Inf. Sci. (2012)
Keyphrases
- upper bound
- number of hidden neurons
- neural network
- multilayer perceptron
- hidden layer
- hidden neurons
- single hidden layer
- activation function
- artificial neural networks
- lower bound
- back propagation
- learning rate
- feedforward neural networks
- feed forward
- feed forward neural networks
- radial basis function
- worst case
- extreme learning machine
- recurrent neural networks
- neural network model
- pattern recognition
- neural nets
- network architecture
- fuzzy logic
- input variables
- training algorithm
- generalization ability
- training speed
- multi layer perceptron
- error function
- radial basis function neural network
- high dimensional
- objective function
- feature extraction
- learning algorithm