Artificial Neural Networks

Lecturer:

Mirko Novák (gar.)

Tutor:

Mirko Novák (gar.)

Supervisor:

Department of Control and Telematics

Synopsis:

Basic knowledge in the field of neural networks, their classification and application.

Requirements:

Basic knowledge of mathematics.

Syllabus of lectures:

History of neural networks. Basic principles. Comparing the structure of a natural and an artificial neuron. Neural classificators, predictors, compresors, expanders and other specialised functional regulators. Modelling of neurons. Grossberg's equations. Learning principles. Hopfield's nets. Information and control tasks solution in transportation and other areas.

Syllabus of tutorials:

Study Objective:

Study materials:

Novák M., Kufufaki O., Moos P., Musílek P., Pelikán E., Šebesta V.: Umělé neuronové sítě, teorie a aplikace, Praha, C.H. Beck, 1998,

Fogelman Soulié F., Gallinari P.: Industrial applications of neural networks, Singapore, World Scientific, 1998,

Norgaard M., Ravn O., Poulsen N. K., Hansen L. K.: Neural Networks for Modelling and Control of Dynamic

Note:

Time-table for winter semester 2011/2012:

Time-table is not available yet

Time-table for summer semester 2011/2012:

Time-table is not available yet

The course is a part of the following study plans: