The artificial intelligence has its origins in the fortieths of the twentieth century. In 1943 McCulloch and Pitts elaborated model of human and animal neuron and explained the principles of combination of neurons i.e. neural network. Further advancement in this field of science contributed to introduction and design of perceptron (Rosenblatt, 1958). Its task was to recognise alphanumeric signs. There were also attempts to use neural networks among other things to weather forecast, identification of mathematical formulas, or analysis of electrocardiogram.

     In 1969 Minski and Papert published the monograph in which they proved that one-layer perceptron-like nets has limited area of application. This fact discouraged scientists from working on perceptrons and moved theirs interests towards expert systems. In the middle of the eighties some papers which proved that multi-layer non-linear neural networks has not limitations appeared. It caused growth of interests of this field of knowledge. The technology development of VLSI integrated circuits contributed to improvement of neuro-computers in the same period of time. The very important achievements are different training methods of multi-layer neural networks, e.g. back-propagation algorithm.