Unified Analysis on the Global Dissipativity and Stability of Fractional-Order Multidimension-Valued Memristive Neural Networks With Time Delay
Unified Analysis on the Global Dissipativity and Stability of Fractional-Order Multidimension-Valued Memristive Neural Networks With Time Delay
复制标题
分数阶多维值时滞忆阻神经网络的全局耗散性和稳定性的统一分析
DOI：
10.1109/tnnls.2021.3071183
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发表时间：
2021-05
影响因子：
10.4
通讯作者：
Jianying Xiao;S. Zhong;S. Wen
中科院分区：
文献类型：
--
作者：
Jianying Xiao;S. Zhong;S. Wen
分析了分数阶时滞多维值忆阻神经网络（FSMVMNN）系统的全局耗散性和稳定性的统一判据。首先，基于多维代数、分数阶导数和非光滑分析的综合知识，建立了所研究的FSMVMNN的统一模型，提出了一种更为统一的多维神经网络动力学行为分析方法。然后，主要应用李雅普诺夫方法，采用几个新引理，解决一些数学难题，不作任何分离，得到了统一而简洁的准则。该准则具有计算量小、保守性低、多样性强、灵活性高等优点。最后，我们提供了两个数值例子来说明理论结果的有效性和改进。
The unified criteria are analyzed on the global dissipativity and stability for the delayed fractional-order systems of multidimension-valued memristive neural networks (FSMVMNNs) in this article. First, based on the comprehensive knowledge about multidimensional algebra, fractional derivatives, and nonsmooth analysis, we establish the unified model for the studied FSMVMNNs in order to propose a more uniform method to analyze the dynamic behaviors of multidimensional neural networks. Then, by mainly applying the Lyapunov method, employing several new lemmas, and solving some mathematical difficulties, without any separation, we acquire the unified and concise criteria. The derived criteria have many advantages in a smaller calculation, lower conservatism, more diversity, and higher flexibility. Finally, we provide two numerical examples to express the availability and improvements of the theoretical results.