In this study, we investigate the global exponential stability of Clifford-valued neural network (NN) models with impulsive effects and time-varying delays. By taking impulsive effects into consideration, we firstly establish a Clifford-valued NN model with time-varying delays. The considered model encompasses real-valued, complex-valued, and quaternion-valued NNs as special cases. In order to avoid the issue of non-commutativity of the multiplication of Clifford numbers, we divide the original n-dimensional Clifford-valued model into \(2^{m}n\)-dimensional real-valued models. Then we adopt the Lyapunov–Krasovskii functional and linear matrix inequality techniques to formulate new sufficient conditions pertaining to the global exponential stability of the considered NN model. Through numerical simulation, we show the applicability of the results, along with the associated analysis and discussion.

在这项研究中，我们研究具有脉冲效应和时变时滞的Clifford值神经网络（NN）模型的全局指数稳定性。通过考虑脉冲效应，我们首先建立了具有时变时滞的Clifford值NN模型。考虑的模型包括实值，复值和四元数值的NN，作为特例。为了避免Clifford数乘法的不可交换性问题，我们将原始n维Clifford值模型划分为\（2 ^ {m} n \）维实值模型。然后，我们采用Lyapunov–Krasovskii泛函和线性矩阵不等式技术来制定与考虑的NN模型的全局指数稳定性有关的新的充分条件。通过数值模拟，我们显示了结果的适用性，以及相关的分析和讨论。