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Some promising mathematical model of neural network

Keywords:

Yu.Yu. Petrunin – Dr.Sc. (Philos.), Professor, Head of Department of Mathematical Methods and Information Technology in Management, School of Public Administration, Lomonosov Moscow State University
E-mail: petrunin@spa.msu.ru


The McCulloch-Pitts neural model is a simplification of the nervous system of humans and other living beings. These models do not reflect the complexity of human intellectual activity. These models are unable to explain the process of adaptation of living beings to a constantly changing external environment.
In modern science there are more advanced and promising models of neuron and modelsneural network. These models developed by Russian scientists A.A. Zhdanov and A.V. Savelyev. Original ideas and models of the Russian scientists outlined in [1–9]. A.A. Zhdanov models the human brain (intellect) with systems of autonomous adaptive control. These systems are self-learning recognition and control systems. From the point A.A. Zhdanov, the nervous system is, first of all, an adaptive control machine. Ideas and models Savelyev rely on modern neurophysiological and cybernetic results of research on human intellectual activity.
The models of A.A. Zhdanov and A.V. Savelyev patented. However, this is not enough. Currently, scientists use computer programs based on traditional the McCulloch-Pitts neural model (NeuroShell, Statistica Neural Networks, etc.).
Now there is a need to create a publicly available computer programs based on those neural network models.

References:
  1. Zhdanov A.A. Avtonomny'j iskusstvenny'j intellekt. M.: Binom. 2012.
  2. Savel'ev A.V. Iskusstvenny'j nerv // Biomediczinskaya radioe'lektronika. 2017. № 2. S. 57–65.
  3. Bryanczev I.S., Kolushov V.V., Savel'ev A.V. Ot nejrofilosofii k nejronaukovedeniyu: kod polozheniya nejrona material'ny'j substrat kodov soznaniya? // Biomediczinskaya radioe'lektronika. 2016. № 4. S. 8–11.
  4. Savel'ev A.V. Otkry'tie nejrofizicheskix vixrej v nervnoj sisteme // Biomediczinskaya radioe'lektronika. 2015. № 6. S. 15–27.
  5. Savel'ev A.V. Osobennosti e'lektroximicheskogo vixrevogo rasprostraneniya spajkov v aksonal'noj sisteme nejronov // Biomediczinskaya radioe'lektronika. 2012. № 8. S. 71–72.
  6. Stepanyan I.V., Javelov I.S., Savel'ev A.V., O Xan Do, Svirin V.I., Pleshakov K.V. Fazoimpul'sny'j analiz pul'sovoj volny' i biopotenczialov mozga cheloveka // Biomediczinskaya radioe'lektronika. 2015. № 4. C. 81–83.
  7. Bryanczev I.S., Kolushov V.V., Ryazanov M.A., Savel'ev A.V. Modelirovanie nejroproczessorny'x svojstv dendritov nejronov i sistemnoe reshenie problemy' distal'ny'x sinapsov // Nejrokomp'yutery': razrabotka, primenenie. 2015. № 8. S. 20–32.
  8. Petrunin Ju.Ju., Ryazanov M.A., Savel'ev A.V. Ot iskusstvennogo intellekta k modelirovaniyu mozga. M. 2014.
  9. Kolushov V.V., Savel'ev A.V. Supervizualizaczionnaya biomexanodinamika sverxslozhny'x sistem // Biomediczinskaya radioe'lektronika. 2015. № 4. S. 37–39.

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