具有脉冲的中立型随机时滞神经网络的稳定性分析
Stability Analysis of Neutral-Type Stochastic Delay Neural Networks with Impulsive E?ects
摘要: 本文研究了一类同时受到脉冲和随机扰动影响的中立型神经网络系统的均方指数稳定性。通过引入局部可积的脉冲密度函数与相应的脉冲强度约束，构造适当的 Lyapunov–Krasovskii 泛函，运用改进的Razumikhin方法，得到了稳定的充分性判据。最后给出数值示例，并运用MATLAB仿真，验证结果的正确性和可行性。
Abstract: This paper investigates the mean-square exponential stability of a class of neutral-type neural network systems subject to both impulsive effects and stochastic disturbances. By introducing a locally integrable impulse density function and corresponding impulse strength constraints, an appropriate Lyapunov–Krasovskii functional is constructed. Using the improved Razumikhin method, a set of sufficient criteria for stability is established. Finally, numerical examples and MATLAB simulations are provided to verify the correctness and feasibility of the theoretical results.
文章引用：张松, 孙小淇. 具有脉冲的中立型随机时滞神经网络的稳定性分析[J]. 应用数学进展, 2026, 15(2): 408-423. https://doi.org/10.12677/AAM.2026.152081

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