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

Dr. Nils Goerke

Tuesdays 8:15-9:45

Lecture Hall: LBH, III.03a

Lecture starts on Tuesday, 15 Oct 2013, 8:15 o'clock, Lecture Hall LBH, III.03a

Results from the Exam are available on the exercises homepage

Re-sit Examination

The re-sit examination will be on Tuesday 25 March 2014, 9:00-10:40, Room LBH, HS-III.03

TNN-Exercises Homepage

Please notice: There are no prerequisites for Master of Computer Science students for this module in Winter 2012.
The lecture is organised as 2hrs lecture plus 2 hrs exercises per week in the time from Tuesday 15 Oct 2013 to Fr 1 Feb 2013.
The lecture starts on:Tuesday, 15 Oct 2013, 8:15 o'clock, Lecture Hall LBH, III.03a .

This lecture is part of the intelligent systems track of the master programme "Computer Science". It is open for CS diploma students (B).

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.