G.M. Alakoz - Dr.Sc. (Eng.), Professor, Russian Academy of Rocket and Artillery Sciences Councilor (Moscow) E-mail: gen1nor2@gmail.com A.S. Dobrotvorsky - Systems Engineer, ANO Institute of Behavior (Moscow) E-mail: dobrotvorskiy@gmail.com M.M. Kolleganov - Systems Programmer ANO Institute of Behavior (Moscow) E-mail: shumi.arrow@gmail.com A.A. Popov - Ph.D. (Eng.), Systems Analyst ANO Institute of Behavior (Moscow) E-mail: voterim@mail.ru R.V. Svetlov - Systems Programmer ANO Institute of Behavior (Moscow) E-mail: svetlovroman@gmail.com A.A. Salomatov - Ph.D. (Eng.), Systems Analyst ANO Institute of Behavior (Moscow)

Neuron model in the form of rangotron allows investigating mechanisms that are more adequate by its morphofunctional properties to real neurons than preceding formal neuron models, so as: relies on non-numerical data transformation methods based on the «weighing» mechanism of beam scales; uses delay time as functionally significant factor creating «complication» effect at macro-level not quantum register state, but input actions. Such a profound analogy between quantum registers and rangotron makes itself evident in the fact that the source of ultrahigh parallelelism coefficients is «ambiguous» mapping {Xn(T)}Nfs, and transition to single-valued transformation Xn(T)fs is performed by «external» measuring system. Furthermore in rangotron as in quantum register «virtual» parallelelism coefficient of Boolean functions (by «input») is constant and equals =2n. «Virtuality» comprehends that at any point of time performed by rangotron mapping F: Xnfsapplies to all Xn(){Xn(T)}N, despite the fact that current rank R[Xn(T)] as well as output rangatron reaction fs are determined by the contents of base position .

 

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