Passivity analysis of impulsive coupled reaction-diffusion neural networks with and without time-varying delay

Wei, Pu-Chong; Wang, Jinliang; Huang, Yanli; Xu, Beibei; Ren, Shun-Yan

doi:10.1016/j.neucom.2015.06.021

Cited by 23 publications

(2 citation statements)

References 39 publications

(42 reference statements)

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“…From this point, diffusion phenomena should not be ignored in neural networks. Many good results about reaction-diffusion neural networks have been obtained [21][22][23][24][25]. The boundary conditions in most literatures listed are assumed to be Dirichlet boundary conditions.…”

Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

Adaptive Exponential Synchronization for Stochastic Competitive Neural Networks with Time-Varying Leakage Delays and Reaction-Diffusion Terms

Wang

2017

Mathematical Problems in Engineering

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We study the exponential synchronization problem for a class of stochastic competitive neural networks with different timescales, as well as spatial diffusion, time-varying leakage delays, and discrete and distributed time-varying delays. By introducing several important inequalities and using Lyapunov functional technique, an adaptive feedback controller is designed to realize the exponential synchronization for the proposed competitive neural networks in terms of -norm. According to the theoretical results obtained in this paper, the influences of the timescale, external stimulus constants, disposable scaling constants, and controller parameters on synchronization are analyzed. Numerical simulations are presented to show the feasibility of the theoretical results.

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Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

Adaptive Exponential Synchronization for Stochastic Competitive Neural Networks with Time-Varying Leakage Delays and Reaction-Diffusion Terms

Wang

2017

Mathematical Problems in Engineering

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“…In the past decade, many researchers have drawn increasing attention to dynamical analysis of complex dynamical networks due to a variety of their application fields, such as biology, physics, mathematics, sociology and so on [1][2][3][4][5][6]. On the basis of complex network models, the complex dynamical networks have been extensively investigated, especially in the interaction between the overall structure and complexity, and the local dynamical properties of the coupled nodes.…”

Section: Introductionmentioning

confidence: 99%

Pinning and adaptive synchronization of fractional-order complex dynamical networks with and without time-varying delay

Wang

Ruan

et al. 2018

Adv Differ Equ

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The synchronization problem for a class of fractional-order complex dynamical networks with and without time-varying delay is investigated in this paper. By utilizing generalized Barbalat's lemma, Razumikhin-type stability theory and matrix inequality technique, some sufficient criteria ensuring synchronization under pinning control and pinning adaptive feedback control are derived. Finally, three numerical simulations are presented to demonstrate the effectiveness of the obtained results.

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Introduction

Wang¹,

Wu²,

Ren³

2020

Passivity of Complex Dynamical Networks

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Passivity analysis of impulsive coupled reaction-diffusion neural networks with and without time-varying delay

Cited by 23 publications

References 39 publications

Adaptive Exponential Synchronization for Stochastic Competitive Neural Networks with Time-Varying Leakage Delays and Reaction-Diffusion Terms

Adaptive Exponential Synchronization for Stochastic Competitive Neural Networks with Time-Varying Leakage Delays and Reaction-Diffusion Terms

Pinning and adaptive synchronization of fractional-order complex dynamical networks with and without time-varying delay

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