Construction and Optimization of Stability Conditions of Learning Processes in Mathematical Models of Neurodynamics

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F22%3APU150350" target="_blank" >RIV/00216305:26220/22:PU150350 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Construction and Optimization of Stability Conditions of Learning Processes in Mathematical Models of Neurodynamics

Popis výsledku v původním jazyce

This article is devoted to dynamic processes in the field of artificial intelligence, namely in the tasks of neurodynamics: the field of knowledge in which neural networks are considered as nonlinear dynamical systems and focuses on the problem of stability. The systems under consideration share four common characteristics: a large number of nodes (neurons), nonlinearity, dissipativity, noise. The purpose of this work is to build to construct of asymptotic stability conditions for dynamic model of neuronet network, which is described in terms of ODE nonlinear systems. Main method of investigation is Lyapunov direct method. Authors show that solution of pointed problem can be reduced to the task of convex optimization. By realization on Python tools the algorithm of Nelder-Mead method, a number of numerical experiments were conducted to select the optimal parameters of the Lyapunov function.

Název v anglickém jazyce

Construction and Optimization of Stability Conditions of Learning Processes in Mathematical Models of Neurodynamics

Popis výsledku anglicky

This article is devoted to dynamic processes in the field of artificial intelligence, namely in the tasks of neurodynamics: the field of knowledge in which neural networks are considered as nonlinear dynamical systems and focuses on the problem of stability. The systems under consideration share four common characteristics: a large number of nodes (neurons), nonlinearity, dissipativity, noise. The purpose of this work is to build to construct of asymptotic stability conditions for dynamic model of neuronet network, which is described in terms of ODE nonlinear systems. Main method of investigation is Lyapunov direct method. Authors show that solution of pointed problem can be reduced to the task of convex optimization. By realization on Python tools the algorithm of Nelder-Mead method, a number of numerical experiments were conducted to select the optimal parameters of the Lyapunov function.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

20205 - Automation and control systems

Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

9th International Scientific Conference "Information Technology and Implementation"

ISBN

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ISSN

1613-0073

e-ISSN

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Počet stran výsledku

10

Strana od-do

1-10

Název nakladatele

CEUR-WS

Místo vydání

neuveden

Místo konání akce

Kyiv

Datum konání akce

30. 11. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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