On Asymptotic Properties of Stochastic Neutral-Type Inertial Neural Networks with Mixed Delays
This article studies the stability problem of a class of stochastic neutral-type inertial delay neural networks. By introducing appropriate variable transformations, the second-order differential system is transformed into a first-order differential system. Using homeomorphism mapping, standard stoc...
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Format: | Article |
Language: | English |
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MDPI AG
2023-09-01
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Series: | Symmetry |
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Online Access: | https://www.mdpi.com/2073-8994/15/9/1746 |
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author | Bingxian Wang Honghui Yin Bo Du |
author_facet | Bingxian Wang Honghui Yin Bo Du |
author_sort | Bingxian Wang |
collection | DOAJ |
description | This article studies the stability problem of a class of stochastic neutral-type inertial delay neural networks. By introducing appropriate variable transformations, the second-order differential system is transformed into a first-order differential system. Using homeomorphism mapping, standard stochastic analyzing technology, the Lyapunov functional method and the properties of a neutral operator, we establish new sufficient criteria for the unique existence and stochastically globally asymptotic stability of equilibrium points. An example is also provided, to show the validity of the established results. From our results, we find that, under appropriate conditions, random disturbances have no significant impact on the existence, stability, and symmetry of network systems. |
first_indexed | 2024-03-10T21:54:23Z |
format | Article |
id | doaj.art-40751745341c47d2bdb9dcfe29bbcb92 |
institution | Directory Open Access Journal |
issn | 2073-8994 |
language | English |
last_indexed | 2024-03-10T21:54:23Z |
publishDate | 2023-09-01 |
publisher | MDPI AG |
record_format | Article |
series | Symmetry |
spelling | doaj.art-40751745341c47d2bdb9dcfe29bbcb922023-11-19T13:12:04ZengMDPI AGSymmetry2073-89942023-09-01159174610.3390/sym15091746On Asymptotic Properties of Stochastic Neutral-Type Inertial Neural Networks with Mixed DelaysBingxian Wang0Honghui Yin1Bo Du2School of Mathematics and Statistics, Huaiyin Normal University, Huaian 223300, ChinaSchool of Mathematics and Statistics, Huaiyin Normal University, Huaian 223300, ChinaSchool of Mathematics and Statistics, Huaiyin Normal University, Huaian 223300, ChinaThis article studies the stability problem of a class of stochastic neutral-type inertial delay neural networks. By introducing appropriate variable transformations, the second-order differential system is transformed into a first-order differential system. Using homeomorphism mapping, standard stochastic analyzing technology, the Lyapunov functional method and the properties of a neutral operator, we establish new sufficient criteria for the unique existence and stochastically globally asymptotic stability of equilibrium points. An example is also provided, to show the validity of the established results. From our results, we find that, under appropriate conditions, random disturbances have no significant impact on the existence, stability, and symmetry of network systems.https://www.mdpi.com/2073-8994/15/9/1746neutral-type inertial neural networksstochasticstabilitydelays |
spellingShingle | Bingxian Wang Honghui Yin Bo Du On Asymptotic Properties of Stochastic Neutral-Type Inertial Neural Networks with Mixed Delays Symmetry neutral-type inertial neural networks stochastic stability delays |
title | On Asymptotic Properties of Stochastic Neutral-Type Inertial Neural Networks with Mixed Delays |
title_full | On Asymptotic Properties of Stochastic Neutral-Type Inertial Neural Networks with Mixed Delays |
title_fullStr | On Asymptotic Properties of Stochastic Neutral-Type Inertial Neural Networks with Mixed Delays |
title_full_unstemmed | On Asymptotic Properties of Stochastic Neutral-Type Inertial Neural Networks with Mixed Delays |
title_short | On Asymptotic Properties of Stochastic Neutral-Type Inertial Neural Networks with Mixed Delays |
title_sort | on asymptotic properties of stochastic neutral type inertial neural networks with mixed delays |
topic | neutral-type inertial neural networks stochastic stability delays |
url | https://www.mdpi.com/2073-8994/15/9/1746 |
work_keys_str_mv | AT bingxianwang onasymptoticpropertiesofstochasticneutraltypeinertialneuralnetworkswithmixeddelays AT honghuiyin onasymptoticpropertiesofstochasticneutraltypeinertialneuralnetworkswithmixeddelays AT bodu onasymptoticpropertiesofstochasticneutraltypeinertialneuralnetworkswithmixeddelays |