{"title":"Global exponential stability of periodic solutions for inertial delayed BAM neural networks","authors":"Wentao Wang , Wei Zeng , Wei Chen","doi":"10.1016/j.cnsns.2025.108728","DOIUrl":null,"url":null,"abstract":"<div><div>In this paper, we utilize the characteristic method to establish new sufficient conditions for the global exponential stability of periodic solutions for inertial delayed bidirectional associative memory (BAM) neural networks. The proposed criteria are presented as a series of linear scalar inequalities, which notably circumvent the use of the reduced order method and Lyapunov–Krasovskii functionals (LKFs), distinguishing them from prior results and offering simple solvability. Finally, we corroborate the analytical findings through three numerical examples supported by their corresponding simulations.</div></div>","PeriodicalId":50658,"journal":{"name":"Communications in Nonlinear Science and Numerical Simulation","volume":"145 ","pages":"Article 108728"},"PeriodicalIF":3.4000,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communications in Nonlinear Science and Numerical Simulation","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S100757042500139X","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we utilize the characteristic method to establish new sufficient conditions for the global exponential stability of periodic solutions for inertial delayed bidirectional associative memory (BAM) neural networks. The proposed criteria are presented as a series of linear scalar inequalities, which notably circumvent the use of the reduced order method and Lyapunov–Krasovskii functionals (LKFs), distinguishing them from prior results and offering simple solvability. Finally, we corroborate the analytical findings through three numerical examples supported by their corresponding simulations.
期刊介绍：
The journal publishes original research findings on experimental observation, mathematical modeling, theoretical analysis and numerical simulation, for more accurate description, better prediction or novel application, of nonlinear phenomena in science and engineering. It offers a venue for researchers to make rapid exchange of ideas and techniques in nonlinear science and complexity.
The submission of manuscripts with cross-disciplinary approaches in nonlinear science and complexity is particularly encouraged.
Topics of interest:
Nonlinear differential or delay equations, Lie group analysis and asymptotic methods, Discontinuous systems, Fractals, Fractional calculus and dynamics, Nonlinear effects in quantum mechanics, Nonlinear stochastic processes, Experimental nonlinear science, Time-series and signal analysis, Computational methods and simulations in nonlinear science and engineering, Control of dynamical systems, Synchronization, Lyapunov analysis, High-dimensional chaos and turbulence, Chaos in Hamiltonian systems, Integrable systems and solitons, Collective behavior in many-body systems, Biological physics and networks, Nonlinear mechanical systems, Complex systems and complexity.
No length limitation for contributions is set, but only concisely written manuscripts are published. Brief papers are published on the basis of Rapid Communications. Discussions of previously published papers are welcome.
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