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.
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.