A Model of a Universal Neural Computer with Hysteresis Dynamics for Avionics Problems

The paper proposes a method for implementing a universal neural network processor with hysteresis dynamics. This processor allows a wide range of heterogeneous tasks in real time to be performed without reprogramming and changing their internal structure. Adding hysteresis behavior to the system mak...

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Main Authors: Andrey M. Solovyov, Nikolay I. Selvesyuk, Vladislav V. Kosyanchuk, Evgeniy Y. Zybin
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Mathematics
Subjects:
Online Access:https://www.mdpi.com/2227-7390/10/14/2390
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author Andrey M. Solovyov
Nikolay I. Selvesyuk
Vladislav V. Kosyanchuk
Evgeniy Y. Zybin
author_facet Andrey M. Solovyov
Nikolay I. Selvesyuk
Vladislav V. Kosyanchuk
Evgeniy Y. Zybin
author_sort Andrey M. Solovyov
collection DOAJ
description The paper proposes a method for implementing a universal neural network processor with hysteresis dynamics. This processor allows a wide range of heterogeneous tasks in real time to be performed without reprogramming and changing their internal structure. Adding hysteresis behavior to the system makes it possible to increase resistance to external influences, the complexity as well as non-linearity of intelligent output. The paper discusses the use of this processor as part of an on-board intelligent avionics system.
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spelling doaj.art-70dcde20cc164948b59b0f0596e9559f2023-12-01T22:24:28ZengMDPI AGMathematics2227-73902022-07-011014239010.3390/math10142390A Model of a Universal Neural Computer with Hysteresis Dynamics for Avionics ProblemsAndrey M. Solovyov0Nikolay I. Selvesyuk1Vladislav V. Kosyanchuk2Evgeniy Y. Zybin3JSC “Concern “Sozvezdie”, Plekhanovskaya Str. 14, 394018 Voronezh, RussiaState Research Institute of Aviation Systems, Viktorenko Str. 7, 125167 Moscow, RussiaState Research Institute of Aviation Systems, Viktorenko Str. 7, 125167 Moscow, RussiaState Research Institute of Aviation Systems, Viktorenko Str. 7, 125167 Moscow, RussiaThe paper proposes a method for implementing a universal neural network processor with hysteresis dynamics. This processor allows a wide range of heterogeneous tasks in real time to be performed without reprogramming and changing their internal structure. Adding hysteresis behavior to the system makes it possible to increase resistance to external influences, the complexity as well as non-linearity of intelligent output. The paper discusses the use of this processor as part of an on-board intelligent avionics system.https://www.mdpi.com/2227-7390/10/14/2390neural network processoravionicson-board intelligent systemdecision support systemhysteretic neural networkhysteresis
spellingShingle Andrey M. Solovyov
Nikolay I. Selvesyuk
Vladislav V. Kosyanchuk
Evgeniy Y. Zybin
A Model of a Universal Neural Computer with Hysteresis Dynamics for Avionics Problems
Mathematics
neural network processor
avionics
on-board intelligent system
decision support system
hysteretic neural network
hysteresis
title A Model of a Universal Neural Computer with Hysteresis Dynamics for Avionics Problems
title_full A Model of a Universal Neural Computer with Hysteresis Dynamics for Avionics Problems
title_fullStr A Model of a Universal Neural Computer with Hysteresis Dynamics for Avionics Problems
title_full_unstemmed A Model of a Universal Neural Computer with Hysteresis Dynamics for Avionics Problems
title_short A Model of a Universal Neural Computer with Hysteresis Dynamics for Avionics Problems
title_sort model of a universal neural computer with hysteresis dynamics for avionics problems
topic neural network processor
avionics
on-board intelligent system
decision support system
hysteretic neural network
hysteresis
url https://www.mdpi.com/2227-7390/10/14/2390
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