Introduction to the Theory of Neural Computation

Units Weight Pattern simple Vector Perceptron Adaptive Resonance Theory Output Gradient Descent Unit Input Unsupervised learning Hopfield Model Vice Versa Receptive Fields Anders Krogh Binary Threshold Units Boltzmann Machine hidden Feed Forward Networks Counter-propagation Networks Generalization Ability Hebb Rule Hopfield Network Input Output Pairs John Hertz Input Pattern Hidden Units Richard G. Palmer Kohonen Feature Mapping Recurrent Back Propagation Linearly Independent Simple Perceptron Output Unit Weight Vector Travelling Salesman Problem Terminal Attractors Weighted Matching Problem