Novel delay-dependent stability condition for mixed delayed stochastic neural networks with leakage delay signals

ABSTRACT

In this paper, the problem of stability condition for mixed delayed stochastic neural networks with neutral delay and leakage delay is investigated. A novel Lyapunov functional is constructed with double and triple integral terms. New sufficient conditions are derived to guarantee the global asymptotic stability of the concerned neural network. This paper is more general than the paper by Zhu et al. [Robust stability of Markovian jump stochastic neural networks with time delays in the leakage terms, Neural Process. Lett. 41 (2015), pp. 1–27]. In our paper, we considered both the neutral delay and leakage delay, but the paper by Zhu et al. is not considering the neutral delay. Also we employed triple integrals in the Lyapunov functional which is not used in the paper by Zhu et al. Finally, two numerical examples are provided to show the effectiveness of the theoretical results.

KEYWORDS:

• Asymptotic stability
• linear matrix inequality
• Lyapunov–Krasovskii functional
• stochastic neural network
• time-varying delay

2010 AMS SUBJECT CLASSIFICATIONS:

• 93D05
• 93D09
• 93D20

Disclosure statement

No potential conflict of interest was reported by the authors.