Exponential Lagrange stability for impulses in discrete-time delayed recurrent neural networks

Wenlin Jiang, Liangliang Li, Zhengwen Tu and Yuming Feng

International Journal of Systems Science, 2019, vol. 50, issue 1, 50-59

Abstract: This paper focuses on the problem of exponential stability in the sense of Lagrange for impulses in discrete-time delayed recurrent neural networks. By establishing a delayed impulsive discrete inequality and a novel difference inequality, combining with inequality techniques, some novel sufficient conditions are obtained to ensure exponential Lagrange stability for impulses in discrete-time delayed recurrent neural networks. Meanwhile, exponentially convergent scope of neural network is given. Finally, several numerical simulations are given to demonstrate the effectiveness of our results.

Date: 2019
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DOI: 10.1080/00207721.2018.1543475

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