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New Results on Interval General Cohen-Grossberg BAM Neural Networks
Journal of Systems Science and Complexity ( IF 2.6 ) Pub Date : 2020-08-08 , DOI: 10.1007/s11424-020-8048-9
Chaouki Aouiti , Farah Dridi

This paper is concerned with an interval general Cohen-Grossberg bidirectional associative memory neural networks with mixed delays. Under proper conditions, the authors studied the existence, the uniqueness and the global exponential stability of almost automorphic solutions for the suggested system. The proposed method was mainly based on the exponential dichotomy of linear differential equation, the Banach’s fixed point principle and the differential inequality techniques. The authors illustrate with an example to demonstrate the effectiveness of the proposed findings.

中文翻译:

区间一般Cohen-Grossberg BAM神经网络的新结果

本文涉及具有混合时滞的区间广义Cohen-Grossberg双向联想记忆神经网络。在适当的条件下,作者研究了该系统几乎自同构解的存在性,唯一性和全局指数稳定性。所提出的方法主要基于线性微分方程的指数二分法,Banach不动点原理和微分不等式技术。作者通过一个例子来说明所提出的发现的有效性。
更新日期:2020-08-08
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