Neurocybernetics is a scientific field that studies the basic laws of the organization and functioning of neurons and neural formations. The main method of neurocybernetics is mathematical modeling, while the data of a physiological experiment are used as source material for creating models.
One of the most promising areas of neurocybernetics - at the junction between psychology, biology and computer science - is modeling based on neural networks .
Neurocybernetics has a wide range of applications - from biomedical developments to the creation of specialized neurocomputers .
The term neurocybernetics , used abroad, has a slightly different meaning, similar to bionics . The Russian term neurocybernetics corresponds to another English term, neural engineering .
The first neural networks were created by Rosenblatt and McCallock in 1956–1965. These were attempts to create systems that simulate the human eye and its interaction with the brain. The device created by them then was called the perceptron (perceptron). It was able to distinguish letters of the alphabet, but was sensitive to their spelling. Gradually, in the 70–80s, the number of works in this area of artificial intelligence began to decline. The first results were too disappointing. The authors explained the failure of low memory and low speed of existing computers at that time.
However, in the 1980s, the first neurocomputer was created in Japan as part of the "V Generation Computer" project. By this time, limitations on memory and speed were almost removed.
There are transporters - parallel computers with a large number of processors. Transporter technology is only one of a dozen new approaches to the hardware implementation of neural networks that model the hierarchical structure of the human brain.
Literature
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