Introduction to Neural Computation
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General introduction.

The Hopfield model and other feedback networks.

The perceptron and general feed-forward networks.

Learning and generalization.

Unsupervised Hebbian competitive learning.

Optimization problems.

Selected topics and recent developments.
Independent Component Analysis. Support Vector Machines.

Bibliography:
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* Hertz, Krogh, Palmer: Introduction to the Theory of Neural Computation.

* Bishop: Neural Networks for Pattern Recognition.

* Ripley: Pattern Recognition and Neural Networks.

* Duda, Hart, Stork: Pattern Recognition.

Amit: Modelling Brain Functions.

Peretto: An Introduction to the Modeling of Neural Networks.

Muller and Reinhardt: Neural Networks.

Shepherd: Second-order Methods fo Neural Networks. Springer, 1997.

Scientific American, Sept. 1992.

Kandel, Schwartz, Jessel: Essentials of Neural Science and Behavior.