In this article, we investigate the robust passivity and stability analysis of uncertain complex-valued impulsive neural network (UCVINN) models with time-varying delays. Many practical systems are subject to uncertainty in the real-world environments. As a result, we consider the uncertainty of norm-bounded parameters to achieve more realistic system behaviors. By using appropriate Lyapunov–Krasovskii functionals and integral inequalities, sufficient conditions for the robust passivity and global asymptotic stability of UCVINNs are derived by separating complex-valued neural networks into real and imaginary parts. The criteria are given in terms of linear matrix inequalities (LMIs) that can be checked by the MATLAB LMI toolbox. Finally, numerical simulations are presented to illustrate the merits of the obtained results.

在本文中，我们研究具有时变时滞的不确定复数值脉冲神经网络（UCVINN）模型的鲁棒无源性和稳定性分析。在实际环境中，许多实际系统都存在不确定性。结果，我们考虑了范数有界参数的不确定性，以实现更现实的系统行为。通过使用适当的Lyapunov–Krasovskii泛函和积分不等式，将复值神经网络分为实部和虚部，可以为UCVINN的鲁棒无源性和全局渐近稳定性创造充分条件。这些标准是根据线性矩阵不等式（LMI）给出的，可以通过MATLAB LMI工具箱进行检查。最后，通过数值模拟来说明所获得结果的优点。