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Antiperiodic dynamical behaviors of discontinuous neutral-type Cohen-Grossberg neural networks with mixed time delays

机译:混合时间延迟不连续中性型COHEN-GROSSBERG神经网络的抗哌氏周期动力学行为

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摘要

AbstractThis article presents a class of neutral‐type Cohen‐Grossberg neural networks with discontinuous activations and mixed time delays. Based on the functional differential inclusions theory, inequality technique, and nonsmooth analysis theory with Lyapunovlike approach, some new sufficient criteria are given to ascertain the existence, uniqueness, and globally exponential stability of the antiperiodic solution. Finally, two topical numerical examples and the corresponding computer simulations are delineated to substantiate the correctness of our theoretical predictions. The obtained results of this article are new and complement some related earlier works.
机译:摘要文章介绍了一类中性型COHEN-GROSSBERG神经网络,具有不连续的激活和混合时间延迟。基于功能差分夹杂物理论,不等式技术,与Lyapunovlike方法的不等式技术和非流动分析理论,给出了一些新的足够标准来确定抗哌孕溶液的存在,唯一性和全球指数稳定性。最后,两个局部数值示例和相应的计算机模拟被描绘成证实我们理论预测的正确性。本文所获得的结果是新的,并补充一些相关的早期作品。

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