Artificial Neural Networks, Realization and Applications

Code:
20Y2UA
Academic Degree:
master
Study Programme:
Technology in Transportation and Telecommunications (N 3710)
Form of Study:
full-time study
Credits:
2
Number of Hours:
2 + 0 hours per week - in full-time study
Type of Course:
elective
Semester | Language | Field:
czech all study fields
winter english ERASMUS Teaching for foreign students
Course Completion:
classified credit
Course Tutor:
 
roh  Lectures:
prof. Ing. Mirko Novák, DrSc.
Supervising Department:
Department of Transport Telematics (16120)
Keywords:
neural networks
Abstract:
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 blocs and systems. Modelling of neurons. Grossberg's equations. Learning principles. Leyered and Hopfield's nets.
Objectives:
Basic knowledge in the field of neural networks, their structures, trainning and application. Information and control tasks in transportation and other areas based on neural networks.