1993 IEEE International Conference on Neural Networks, San Francisco, California, March 28-April 1, 1993, Volume 1 |
Contents
San Francisco Hilton Hotel San Francisco California | 8 |
RECURRENT NEURAL NETWORKS I | 33 |
Selfclustering recurrent networksZ Zeng R M Goodman and P Smyth | 39 |
Copyright | |
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activation adaptive filter analog application approach approximation architecture artificial neural networks backpropagation behavior bifurcation classification complex Computer connections constraint convergence corresponding cortex cortical columns cycle dynamic edge edge detection end-effector entropy environment epipolar line equation error example feature feedforward network Figure fixed point function Genetic Algorithms gradient descent hidden units Hopf bifurcation IEEE implementation impulse response initial input patterns interval iterations learning rate linear machine method minimized multiplier neural net neurons node noise nonlinear optimal oscillation parallel parameters PCNN perceptron performance phase pixel placement position prediction problem programming proposed pruning query receptive field recurrent network recurrent neural networks reinforcement representation rule saccade sample selected self-organizing sensor serializable shown in Fig shows sigmoid sigmoid function signal simulation solution solve space Standard EBP step structure synaptic target task threshold tion training data training set update weights