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Sigma-Perceptron, separating hyperplane, Perceptron Learning Algorithm.
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The unique separating hyperplane, Line Search Algorithm.
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Optimal separation via quadratic optimization, Positive kernel, Support Vector Learning.
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K-layer feed-forward networks and sigma-perceptrons. Realizations via k-layers.
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Sigmoid functions, gradient descent, backpropagation algorithm.
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Automatic differentiation and variants of backpropagation.
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Discrete dynamical system, Lyapunov function, attraction, Hopfield network.
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Theorems on fixed points in Hopfield networks, transient length and radius of attraction.
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From Hebbian learning to projection learning.
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