Finite-Time Stability of a Class of CNNs with Heterogeneous Proportional Delays and Oscillating Leakage Coefficients

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• 作者：Bingwen Liu
• 关键词：Cellular neural networks ; Finite ; time stability ; Proportional delay
• 刊名：Neural Processing Letters
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：45
• 期：1
• 页码：109-119
• 全文大小：
• 刊物类别：Physics and Astronomy
• 刊物主题：Artificial Intelligence (incl. Robotics); Complex Systems; Computational Intelligence;
• 出版者：Springer US
• ISSN：1573-773X
• 卷排序：45

文摘

The paper is concerned with the finite-time stability for a class of non-autonomous cellular neural networks with heterogeneous proportional delays and oscillating leakage coefficients. By employing the differential inequality techniques, we establish a novel result to ensure the finite-time stability of the addressed system. Meanwhile, the generalized exponential synchronization is also established. Our approach handles particular cases which were not considered in some early relevant results. An example along with its numerical simulation is presented to demonstrate the validity of the proposed result.