The main goal of this article is to study the global dissipativity problem of Clifford-Valued Multidirectional Associative Memory Neural Networks (CVMAMNNs) with time-varying delays and distributed delays. Based on Lyapunov functionals and Linear Matrix Inequalities (LMIs) approach, new sufficient conditions are derived to ensure the global dissipativity and global exponential dissipativity of the considered network model. Moreover, the global attractive set and global exponential attractive set are obtained which are positive invariant ones. Finally, two numerical examples with simulations are given to illustrate the effectiveness of the analytical findings.

中文翻译：

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具有混合时滞的Clifford值多方向联想记忆神经网络的全局耗散性

本文的主要目的是研究具有时变时滞和分布时滞的Clifford值多方向联想记忆神经网络（CVMAMNN）的全局耗散性问题。基于Lyapunov泛函和线性矩阵不等式（LMI）方法，得出了新的充分条件，以确保所考虑网络模型的全局耗散性和全局指数耗散性。此外，获得了正吸引变量集和全局指数吸引集。最后，给出了两个带有模拟的数值示例，以说明分析结果的有效性。