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Existence and Global Asymptotic Stability of Fuzzy Cellular Neural Networks with Time Delay in the Leakage Term and Unbounded Distributed Delays

机译:具有泄漏项时滞和无界分布时滞的时滞模糊细胞神经网络的存在性和全局渐近稳定性

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Fuzzy cellular neural network (FCNN) structures are based on the uncertainties in human cognitive processes and in modeling neural systems, and they provide an interface between a human expert and classical cellular neural networks (CNNs). In this paper, an existence and global asymptotic stability analysis of the equilibrium point of FCNNs with time delay in the leakage term and unbounded distributed delays is investigated. Based on the Lyapunov-Krasovskii functional with free-weighting matrix, and using the homeomorphism mapping principle and linear matrix inequalities (LMIs), a new set of stability criteria for FCNNs is obtained with time delay in the leakage term, time-varying delays and unbounded distributed delays. The proposed results can be easily checked via the LMI Control Toolbox in MATLAB. Moreover, it is well known that the stability behavior of FCNNs is very sensitive to the time delay in the leakage term. In the absence of the leakage term, a new stability criterion is also derived by employing a Lyapunov-Krasovskii functional using an LMI approach. Numerical examples are provided to illustrate the effectiveness and reduced conservativeness of the developed techniques.
机译:模糊细胞神经网络(FCNN)结构基于人类认知过程和神经系统建模中的不确定性,它们提供了人类专家与经典细胞神经网络(CNN)之间的接口。本文研究了具有泄漏项时滞和无界分布时滞的FCNNs平衡点的存在性和全局渐近稳定性。基于具有自由加权矩阵的Lyapunov-Krasovskii泛函,并利用同胚映射原理和线性矩阵不等式(LMI),获得了一组新的FCNN稳定性准则,其中漏项存在时滞,时变时滞和无限的分布式延迟。可以通过MATLAB中的LMI控制工具箱轻松检查建议的结果。此外,众所周知,FCNN的稳定性对泄漏项中的时间延迟非常敏感。在不存在泄漏项的情况下,通过使用LMI方法使用Lyapunov-Krasovskii泛函还可以得出新的稳定性判据。提供了数值示例来说明所开发技术的有效性和降低的保守性。

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