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LEARNING GENERALIZATION I Poster Presentations
Learning of Category Boundaries Based on Inverse Recall by Multilayer Neural Network II7
A Noniterative Method for Training Feed Forward Networks 1119
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Abstract activity adaptive applied approach approximation artificial neural network associative memory backpropagation behavior binary cells classifier coding Connectionist convergence corresponding criterion defined described distribution dynamical system encoding equations error example feature feedback Figure function fuzzy Gaussian genetic algorithm given gradient gradient descent Grossberg hidden layer hidden units Hopfield hyperspheres IEEE implementation initial input pattern input vector iterations learning algorithm linear mapping matrix method module multilayer neocognitron network architecture neurons node noise nonlinear obtained optimal oscillations output unit paper Parallel Distributed Processing parameters pattern recognition perceptron performance phoneme prediction presented problem propagation proposed pruned random receptive field recurrent recurrent neural network represent representation rule Rumelhart samples Self-Organization sequence shown sigmoid sigmoid function signal simulation space spatial speech speech recognition stability structure subnet synaptic techniques temporal Theorem threshold training data training set unsupervised learning update variables zero