A.V. Savelyev

We investigate the presence and role of cyclic model as a universal paradigm of classical ideas about the mechanisms of higher nervous activity (the concept of I.P. Pavlov, P.K. Anokhin, N.A. Bernstein). It is shown that self-organization of the control algorithms and control structures can only be done with the direct inclusion of the external world or part of a chain of causal events in the acceptor of the results of the functional control systems. The new control concept was based on the main criteria of the time delay characterizing the current situation in real time - of the signal, reaction, etc. With the observability of each elementary step multi-nested cycles are formed that contribute for appearance of complex reverberation-recursive cycles. Such control eliminates the search adaptation and computationally complex optimization procedure. In this case, unlike the optimization procedures that generate irregular problems and lead to an approximate solution, the method can reproduce the changing situation exactly. On this basis the attempt to generalize with the possibility of a general theory has been made. Examples of the use of theoretical achievements were developed in real circuits neuroprocessors and neurocontrollers were protected of patents for inventions. These include neuroprocessors with reverberation emulation, wave neuroprocessors with bio-subprocessors, control of neuron logical properties, multi-reverberation circuitry, control of neuron chaotic properties, based on the proposed concept to auto-fractality. The article discusses some of the results of our work more technical. That is to say, part of the bionic. There is more interesting area of general neurocontrol - biosubstantion control and brain control in varying degrees of understanding of the control ware developed by us in parallel with them also. There is inverse problem - control of technical objects with brain is known now in Russian literature under the name as the «interface brain - computer» or in foreign literature as «neural computer interface». About it - in the following articles.