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Artificial Neural Networks: Basic Concepts
Key Concepts
Activation, Activation function, Artificial neural network (ANN), Artificial neuron, Axon, Binary sigmoid, Code-book vector, Competitive ANN, Correlation learning, Decision plane, Decision surface, Delta learning, Dendrite, Epoch of learning, Euclidean distance, Exemplar, Extended delta rule, Heaviside function, Heb learning, Hebb rule, Hidden layer, Hopfield network, Hyperbolic tangent function, Identity function, Learning rate, Least-mean square (LMS) learning, Linear separability, Logistic sigmoid, McCulloch–Pitts neural model, Multi-layer feed forward, Neuron, Outstar learning, Parallel relaxation, Pattern, Pattern association, Pattern classification, Perceptron, Perceptron convergence ...
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