Search Results - "Babenko, M.G."

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  1. 1

    Transverse-layer partitioning of artificial neural networks for image classification by Vershkov, N.A., Babenko, M.G., Kuchukova, N.N., Kuchukov, V.A., Kucherov, N.N.

    Published in Kompʹûternaâ optika (01-04-2024)
    “…We discuss issues of modular learning in artificial neural networks and explore possibilities of the partial use of modules when the computational resources…”
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    Journal Article
  2. 2

    The architecture of a fault-tolerant modular neurocomputer based on modular number projections by Chervyakov, N.I., Lyakhov, P.A., Babenko, M.G., Lavrinenko, I.N., Lavrinenko, A.V., Nazarov, A.S.

    Published in Neurocomputing (Amsterdam) (10-01-2018)
    “…This paper suggests a rather efficient architecture for an error correction unit of a residue number system (RNS) that is based on a redundant RNS (RRNS) and…”
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  3. 3

    A new model to optimize the architecture of a fault-tolerant modular neurocomputer by Chervyakov, N.I., Lyakhov, P.A., Babenko, M.G., Lavrinenko, I.N., Lavrinenko, A.V., Deryabin, M.A., Nazarov, A.S.

    Published in Neurocomputing (Amsterdam) (16-08-2018)
    “…In this paper, we present some results on error detection and correction in a modular neurocomputer that are based on redundant residue number systems. The…”
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  4. 4

    An efficient method of error correction in fault-tolerant modular neurocomputers by Chervyakov, N.I., Lyakhov, P.A., Babenko, M.G., Garyanina, A.I., Lavrinenko, I.N., Lavrinenko, A.V., Deryabin, M.A.

    Published in Neurocomputing (Amsterdam) (12-09-2016)
    “…In this paper, we propose the architecture of a fault-tolerant unit in a modular neurocomputer that is based on decoding with computation of errors syndromes…”
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  5. 5

    An Approximate Method for Comparing Modular Numbers and its Application to the Division of Numbers in Residue Number Systems by Chervyakov, N. I., Babenko, M. G., Lyakhov, P. A., Lavrinenko, I. N.

    Published in Cybernetics and systems analysis (01-11-2014)
    “…This paper presents a new method and algorithms for dividing modular numbers on the basis of the use of dividend and divisor values relative with respect to…”
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  8. 8

    Efficient Number Comparison in the Residue Number System based on Positional Characteristics by Babenko, M.G., Tchernykh, A.N., Chervyakov, N.I., Kuchukov, V.A., Miranda-López, V., Rivera-Rodriguez, R., Du, Z.

    “…An important operation for data processing is a number comparison. In Residue Number System (RNS), it consists of two steps: the computation of the positional…”
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  9. 9

    Secure and Reliable Data Transmission Over MANET Based On Principles of Computationally Secure Secret Sharing by Chervyakov, N.I., Deryabin, M.A., Nazarov, A.S., Babenko, M.G., Kucherov, N.N., Gladkov, A.V., Radchenko, G.I.

    “…Mobile Ad-Hoc Networks (MANET) require special approaches to the design and selection of data transmission and security algorithms Nodes mobility and dynamic…”
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