Abstract
The bionic model of human cerebral cortex neurons presented in this article is considerably different from the classical model of the McCulloch and Pits formal neuron, since within this model five different types of neuron inputs are distinguished, except for the threshold there is the function describing the neuron potential, and all parameters have a dynamic character. Examples of bionic net building have been considered for the purpose of solution of various problems.
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References
Savelyev, A.V., On the Way to General Theory of Neural Nets. Complexity, Neirokomputery: Razrabotka i Primeneniye (Neurocomputers: Desighn and Application), 2006, nos. 4–5.
Blue Brain Project, http://bluebrain.epfl.ch
Nicholls, J., Martin, R., Wallas, B., and Fuchs, P., From Neuron to Brain, Moscow, Editorial URSS, 2003.
Wasserman, F., Neurocomputer Techniques: Theory and Practice, Moscow, Mir, 1992, 240 p.
Kruglov V.V. and Borisov, V.V., Artificial Neural Networks, Theory and Practice, Moscow, Izd. Goryachaya Liniya-Telecom, 2002.
Berkinblit, M.B., Neural Networks, Moscow, MIROS, 1993.
McCulloch, W. and Pitts, V., Logical calculation of ideas related to nervous activeness, Neurocomputer, 1992, nos. 3–4, pp. 40–50.
Zhadanov, A.A., Method of autonomous adaptive control, Izv. Akad. Nauk. Teoriya i Systemy Upravleniya, (Theory and Control Systems), 1997, vol. 5, no. 2, p. 301–323.
Burtsev, M.S., Gusaev, R.V., and Red’ko, V.G., Model of evolutionary origin of adaptive behavior 1. Case of two requirements, Preprint of IAM RAS, Moscow, 2000, no. 43, see also: http://www.keldysh.ru/pages/BioCyber/PrPrint/PrPrint.htm
Balkenius, C., The Roots of motivations, in From Animals to Animats, Part II, Eds. J.-A. Mayer, H.L. Roitblat, S.W. Wilson, MIT Press, 1993.
Anokhin, P.K., Sistemnye Mekhanizmy Vysshey Nervnoy Deyatelnosti (System Mechanisms of Higher Nervous Activity), Moscow, Nauka, 1979, 453 p.
Anokhin, P.K., Ocherki po Phiziologii Funktsionanykh System (Outlines of Functional Systems Physiology), Moscow, Medicine, 1975.
Anokhin, P.K., Principle Issues of General Theory of Functional Systems, in Printsipy Sistemnoy Organizatsii Funktsiy, Moscow, Nauka, 1973.
Bongard, M.M., Losev, I.S., and Smirnov, M.S., The project of behavior organization model, Animal, in Training and Behavior Modeling, Moscow, Nauka, 1975.
Bongard, M.M., Losev, I.S., Maximov, V.V., and Smirnov, M.S., Formal language of situation description, using the connection concept, in Modelirivaniye Obucheniya i Povedeniya, Moscow, Nauka, 1975.
Weinzveig, M.N. and Polyakova, M.P., Thinking Modeling, 2002, URL: http://www.keldysh.ru/pages/BioCyber/RTA”aintsvaig.htm
Turchin, V.F., Fenomen Nauki. Kiberneticheskiy Podkhod k Evolutsii (Science Phenomenon. Cybernetic Approach to Evolution), Moscow, Nauka, 1993, 295 p., or 2-nd ed., Moscow, ETS, 2000, 368 p.
Jantsch, E., The Self-Organizing Universe, Oxford etc., Pergamon Press, 1980, 340 p.
Heylighen F. and Joslyn, C., Cybernetics and Second Order Cybernetics, in Encyclopedia of Physical Science & Technology, Ed. R.A. Meyers, New York, Academic Press, 2001, vol. 4, 3rd ed., pp. 155–170.
Sutton, R.S. and Barto, A.G., An adaptive network that constructs and uses an internal model of its world, in Cognition and Brain Theory, 1981, vol. 4, pp. 217–246.
Klini, S., Matematicheskaya Logika (Mathematical Logic), Moscow, Mir, 1973, 480 p.
Klopf, A.H., The Hedonistic Neuron: a Theory of Memory, Learning, and Intelligence, Washington etc., Hemisphere publishing corporation, 1982, 140 p.
Sutton, R.S., and Barto, A.G., Toward a modern theory of adaptive networks: Expectation and prediction, Psychological Review, 1981, vol. 88, pp. 135–140.
Valtsev, V.B., Grigoriev, I.R., Lavrov, V.V., and Cherkashin, E.A., Heterogeneous nets and problems of higher brain functions modeling, in Neuroinformatics, Moscow, 2000, pp. 52–56.
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Original Russian Text © S.V. Elkin, S.S. Elkin, E.S. Klyshinskiy, A.A. Kuz’min, V.Yu. Maksimov, 2009, published in Nauchno-Tekhnicheskaya Informatsiya, Seriya 2, 2009, No. 10, pp. 22–32.
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Elkin, S.V., Elkin, S.S., Klyshinskiy, E.S. et al. One model of bionic neural networks. Autom. Doc. Math. Linguist. 43, 296–309 (2009). https://doi.org/10.3103/S0005105509050069
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DOI: https://doi.org/10.3103/S0005105509050069