Realization of Surjective Correspondence in Artificial Neural Network Trained by Fahlman and Lebiere's Learning Algorithm.
Masanori HamamotoKazuki ItoJoarder KamruzzamanYukio KumagaiPublished in: IWANN (1993)
Keyphrases
- artificial neural networks
- learning algorithm
- back propagation
- multilayer perceptron
- multi layer perceptron
- learning rules
- neural network
- feed forward
- training data
- elman network
- training procedure
- bp algorithm
- training samples
- multi layered perceptron
- contrastive divergence
- learning scheme
- reinforcement learning
- machine learning algorithms
- machine learning
- hidden layer
- radial basis function
- genetic algorithm
- active learning
- training algorithm
- learning rate
- training process
- generalization ability
- recurrent neural networks
- supervised learning
- genetic algorithm ga
- training set
- point correspondences
- ann models
- considerable increase
- e learning
- neural network model
- bp neural network
- input variables
- backpropagation neural network
- learning tasks