Technical Neural Networks (4V+2Ü) (MA-INF 4204) [B4]

Dr. Nils Goerke

Mondays and Wednesdays 11-13

Lecture Hall: HS-2

Exercises: 2 hours per week;

Group A: Wed/Mi 13 - 15, Room A7b.
Group B: Thu/Do 11 - 13, Room A6a.
Group C: Thu/Do 15 - 17, Room A6a.

Diese Lehrveranstaltung wird auch als Modul (MA-INF 4204) im Masterstudiengang angeboten und wahrscheinlich in Englisch gehalten.

This lecture is part of the intelligent systems track of the master programme "Computer Science". It is open for CS diploma students [B4].

The lecture gives an overview over the most important technical neural networks and neural paradigms.

The following topics will be explained in detail: Perceptron, multi-layer perceptron (MLP), radial-basis function nets (RBF), Hopfield nets, self organizing feature maps (SOMS, Kohonen), adaptive resonance theory (ART), learning vector quantization, recurrent networks, back-propagation of error, reinforcement learning, Q-learning, support vector machines (SVM), pulse processing neural networks.

In addition exemplary applications of neural nets will be presented and discussed: function approximation, prediction, quality control, image processing, speech processing, action planning, control of technical processes and robots.
Implementation of neural networks in hardware and software: tools, simulators, analog and digital neural hardware.