Technical Neural Networks (L2E4) (MA-INF 4204)

Dr. Nils Goerke

Tuesdays 8:15-9:45

Lecture Hall III.03a, Friedrich-Ebert-Allee 144

Lecture starts on Tuesday, 7 Oct 2014, 8:15 o'clock, Lecture Hall III.03a

TNN-Exercises Homepage

Results from the retake Exam are available:

Inspection of the retake Exam is possible on :

Wednesday 1.4.2015 15:00-16:00, Room: LBH, I.42
Thursday 2.4.2015 10:00-11:00, Room: LBH, I.42
and of course by direct/special appointment with Dr Nils Goerke.

Please have a valid ID (with Photo) with you.

Please notice: There are no prerequisites for Master of Computer Science students for this module in Winter 2014.
The lecture is organised as 2hrs lecture plus 2 hrs exercises per week in the time from Tuesday 7 Oct 2014 to Fr 6 Feb 2015.
The lecture starts on:Tuesday, 7 Oct 2014, 8:15 o'clock, Lecture Hall LBH, III.03a .

This lecture is part of the intelligent systems track of the master programme "Computer Science".

Content of the Lecture:

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), Neocognitron.

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.