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<p>This paper applies Lagrange sense to solve the global exponential stability problem for a class of inertial neural networks with both time-varying delays. The existence of time-varying delays in discrete and distributed terms is investigated using lower and upper bounds. First, we convert the proposed inertial neural networks into regular ones. Second, new brand Lyapunov-Krasovskii functionals, stability theory, and integral inequality are used to develop a number of novel required conditions for the stability of the neural networks under discussion using linear matrix inequalities. The LMI control toolbox in MATLAB software allows for easy testing in real-world circumstances. Several comparisons are made between the planned study and several current literatures in an attempt to further minimize conservatism. Finally, three numerical examples are shown to demonstrate the advantages and superiority of our theoretical results.</p>

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Lagrange stability of inertial type neural networks:  A Lyapunov-Krasovskii functional approach

  • 期刊论文

  • 发表日期：

    2025年5月10日

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  • C. Maharajan,
  • C. Sowmiya,
  • Changjin Xu

摘要

This paper applies Lagrange sense to solve the global exponential stability problem for a class of inertial neural networks with both time-varying delays. The existence of time-varying delays in discrete and distributed terms is investigated using lower and upper bounds. First, we convert the proposed inertial neural networks into regular ones. Second, new brand Lyapunov-Krasovskii functionals, stability theory, and integral inequality are used to develop a number of novel required conditions for the stability of the neural networks under discussion using linear matrix inequalities. The LMI control toolbox in MATLAB software allows for easy testing in real-world circumstances. Several comparisons are made between the planned study and several current literatures in an attempt to further minimize conservatism. Finally, three numerical examples are shown to demonstrate the advantages and superiority of our theoretical results.