New Delay-Dependent Stability Criteria for Impulsive Neural Networks with Additive Time-Varying Delay Components and Leakage Term

  • R. Samidurai
  • S. Rajavel
  • Jinde Cao
  • Ahmed Alsaedi
  • Bashir Ahmad


This work is concerned with the delay-dependent stability problem for uncertain impulsive neural networks (NNs) with additive time-varying delay components and leakage term. We construct a newly augmented Lyapunov–Krasovskii (L–K) functional which contains triple and four integral terms and then utilizing free-matrix-based integral inequality to bound the derivative of the Lyapunov–Krasovskii functional. Some sufficient conditions are derived to assure the delay-dependent stability of the impulsive NNs by the linear matrix inequality, which is less conservative than some existing results and can be readily verified by the convex optimization algorithms. In addition, some information of activation function ignored in previous works has been taken into account in the resulting condition. In the end, three numerical examples are provided to illustrate the effectiveness of the proposed criteria.


Delay-dependent stability Neural networks Linear matrix inequality Additive time-varying delay Leakage delay Lyapunov–Krasovskii functional 



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Authors and Affiliations

  1. 1.Department of MathematicsThiruvalluvar UniversityVelloreIndia
  2. 2.Jiangsu Provincial Key Laboratory of Networked Collective Intelligence, Department of Mathematics, Research Center for Complex Systems and Network SciencesSoutheast UniversityNanjingChina
  3. 3.Nonlinear Analysis and Applied Mathematics (NAAM) Research Group, Department of MathematicsKing Abdulaziz UniversityJeddahSaudi Arabia

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