Artificial Neural Networks

Garant předmětu:

Lecturer:

Tutor:

Supervisor:

Department of Transport 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:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans: