Boundary Controlling Synchronization and Passivity Analysis for Multi-Variable Discrete Stochastic Inertial Neural Networks
The current paper considers discrete stochastic inertial neural networks (SINNs) with reaction diffusions. Firstly, we give the difference form of SINNs with reaction diffusions. Secondly, stochastic synchronization and passivity-based control frames of discrete time and space SINNs are newly formul...
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MDPI AG
2023-08-01
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Online Access: | https://www.mdpi.com/2075-1680/12/9/820 |
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author | Yongyan Yang Tianwei Zhang Zhouhong Li |
author_facet | Yongyan Yang Tianwei Zhang Zhouhong Li |
author_sort | Yongyan Yang |
collection | DOAJ |
description | The current paper considers discrete stochastic inertial neural networks (SINNs) with reaction diffusions. Firstly, we give the difference form of SINNs with reaction diffusions. Secondly, stochastic synchronization and passivity-based control frames of discrete time and space SINNs are newly formulated. Thirdly, by designing a boundary controller and constructing a Lyapunov-Krasovskii functional, we address decision theorems for stochastic synchronization and passivity-based control for the aforementioned discrete SINNs. Finally, to illustrate our main results, a numerical illustration is provided. |
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institution | Directory Open Access Journal |
issn | 2075-1680 |
language | English |
last_indexed | 2024-03-10T23:03:42Z |
publishDate | 2023-08-01 |
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series | Axioms |
spelling | doaj.art-9abd60a5bed34b4695d021d29a666a112023-11-19T09:32:11ZengMDPI AGAxioms2075-16802023-08-0112982010.3390/axioms12090820Boundary Controlling Synchronization and Passivity Analysis for Multi-Variable Discrete Stochastic Inertial Neural NetworksYongyan Yang0Tianwei Zhang1Zhouhong Li2Department of Mathematics, Puyang Petrochemical Vocational and Techenical College, Puyang 457001, ChinaDepartment of Mathematics, Yunnan University, Kunming 650091, ChinaDepartment of Mathematics, Yuxi Normal University, Yuxi 653100, ChinaThe current paper considers discrete stochastic inertial neural networks (SINNs) with reaction diffusions. Firstly, we give the difference form of SINNs with reaction diffusions. Secondly, stochastic synchronization and passivity-based control frames of discrete time and space SINNs are newly formulated. Thirdly, by designing a boundary controller and constructing a Lyapunov-Krasovskii functional, we address decision theorems for stochastic synchronization and passivity-based control for the aforementioned discrete SINNs. Finally, to illustrate our main results, a numerical illustration is provided.https://www.mdpi.com/2075-1680/12/9/820coupled networkspassivity-based controlstochastic synchronizationdiscrete spatial diffusion |
spellingShingle | Yongyan Yang Tianwei Zhang Zhouhong Li Boundary Controlling Synchronization and Passivity Analysis for Multi-Variable Discrete Stochastic Inertial Neural Networks Axioms coupled networks passivity-based control stochastic synchronization discrete spatial diffusion |
title | Boundary Controlling Synchronization and Passivity Analysis for Multi-Variable Discrete Stochastic Inertial Neural Networks |
title_full | Boundary Controlling Synchronization and Passivity Analysis for Multi-Variable Discrete Stochastic Inertial Neural Networks |
title_fullStr | Boundary Controlling Synchronization and Passivity Analysis for Multi-Variable Discrete Stochastic Inertial Neural Networks |
title_full_unstemmed | Boundary Controlling Synchronization and Passivity Analysis for Multi-Variable Discrete Stochastic Inertial Neural Networks |
title_short | Boundary Controlling Synchronization and Passivity Analysis for Multi-Variable Discrete Stochastic Inertial Neural Networks |
title_sort | boundary controlling synchronization and passivity analysis for multi variable discrete stochastic inertial neural networks |
topic | coupled networks passivity-based control stochastic synchronization discrete spatial diffusion |
url | https://www.mdpi.com/2075-1680/12/9/820 |
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