Further results for global exponential stability of stochastic memristor-based neural networks with time-varying delays

Kai Zhong, Song Zhu and Qiqi Yang

International Journal of Systems Science, 2016, vol. 47, issue 15, 3573-3580

Abstract: In recent years, the stability problems of memristor-based neural networks have been studied extensively. This paper not only takes the unavoidable noise into consideration but also investigates the global exponential stability of stochastic memristor-based neural networks with time-varying delays. The obtained criteria are essentially new and complement previously known ones, which can be easily validated with the parameters of system itself. In addition, the study of the nonlinear dynamics for the addressed neural networks may be helpful in qualitative analysis for general stochastic systems. Finally, two numerical examples are provided to substantiate our results.

Date: 2016
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DOI: 10.1080/00207721.2015.1095955

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