An Introduction to Neural Networks
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Included Index.
Properties of single neurons; synaptic integration and neuron models; essential vector operations; lateral inhibition and sensory processing; simple matrix operations; the linear associator - background and foundations; the linear associator - simulations; early network models - the perceptron; gradient descent algorithms; representation of information; applications of simple associators - concept formation and object motion; energy and neural networks - Hopfield networks and Boltzmann machines; nearest neighbour models; adaptive maps; the BSB model - a simple nonlinear autoassociative neural network; associative computation; teaching arithmetic to a neural network.
An Introduction to Neural Networks- The MIT Press-James A. Anderson-1998-EDN-1
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