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Balasundaram, K., Raja, R., Zhu, Q., Chandrasekaran, S. and Zhou, H. (2016) New Global Asymptotic Stability of Discrete-Time Recurrent Neural Networks with Multiple Time-Varying Delays in the Leakage Term and Impulsive Effects. Cognitive Neurodynamics, 214, 420-429.

has been cited by the following article:

• TITLE: New Results of Global Asymptotical Stability for Impulsive Hopfield Neural Networks with Leakage Time-Varying Delay

  AUTHORS: Qiang Xi

  KEYWORDS: Global Asymptotical Stability, Hopfield Neural Networks, Leakage Time-Varying Delay, Impulse, Lyapunov-Kravsovskii Functional, Linear Matrix Inequality

  JOURNAL NAME: Journal of Applied Mathematics and Physics, Vol.5 No.11, November 7, 2017

  ABSTRACT: In this paper, Hopfield neural networks with impulse and leakage time-varying delay are considered. New sufficient conditions for global asymptotical stability of the equilibrium point are derived by using Lyapunov-Kravsovskii functional, model transformation and some analysis techniques. The criterion of stability depends on the impulse and the bounds of the leakage time-varying delay and its derivative, and is presented in terms of a linear matrix inequality (LMI).