Neural networks and learning machines / Simon Haykin.

Includes bibliographical references and index.

-- Rosenblatt's perceptron -- Model building through regression -- The least-mean-square algorithm -- Multilayer perceptrons -- Kernel methods and radial-basis function networks -- Support vector machines -- Regularization theory -- Principal-components analysis -- Self-organizing maps -- Information-theoretic learning models -- Stochastic methods rooted in statistical mechanics -- Dynamic programming -- Neurodynamics -- Bayseian filtering for state estimation of dynamic systems -- Dynamically driven recurrent networks.