Basic vertical-parallel real time neural network components

Methods, algorithms and structures of neural networks were analyzed. Basic components of neural networks were defined and the principles of their development were chosen. It was shown that use of vertical-parallel method for implementation of work algorithms of neural networks basic components provides increased performance, reduce hardware costs and efficient VLSI implementation. Parallel-consequent code converter, which provides time alignment of the processes of data reception and formation of bit sections was developed. The methods of vertical parallel computing were developed: sum of difference squares, due to parallel processing of bit sections, provide performance increase. It was shown that use of developed basic components for neural networks synthesis will provide reduction of time and development cost.