We discuss stability analysis for uncertain stochastic neural networks (SNNs) with time delay in this letter. By constructing a suitable Lyapunov-Krasovskii functional (LKF) and utilizing Wirtinger inequalities for estimating the integral inequalities, the delay-dependent stochastic stability conditions are derived in terms of linear matrix inequalities (LMIs). We discuss the parameter uncertainties in terms of norm-bounded conditions in the given interval with constant delay. The derived conditions ensure that the global, asymptotic stability of the states for the proposed SNNs. We verify the effectiveness and applicability of the proposed criteria with numerical examples.

中文翻译：

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基于 Wirtinger 的积分不等式对延迟随机神经网络的鲁棒稳定性分析

我们在这封信中讨论了具有时间延迟的不确定随机神经网络 (SNN) 的稳定性分析。通过构建合适的 Lyapunov-Krasovskii 泛函 (LKF) 并利用 Wirtinger 不等式估计积分不等式，根据线性矩阵不等式 (LMI) 推导出延迟相关的随机稳定性条件。我们根据具有恒定延迟的给定间隔内的范数有界条件讨论参数不确定性。导出的条件确保了所提出的 SNN 状态的全局渐近稳定性。我们通过数值例子验证了所提出标准的有效性和适用性。