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A Novel Delay-Dependent Criterion for Global Power Stability of Cellular Neural Networks with Proportional Delay

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Abstract

The global power stability of a class of cellular neural networks with proportional delay is considered in this paper. By proposing a new integral inequality and constructing a Lyapunov functional candidate, a novel delay-dependent condition formulated by linear matrix inequalities is derived to ensure that the equilibrium point of the addressed networks achieves global power stability. The proposed criteria complement and improve some existing results in the recent publications, and their effectiveness and advantage are demonstrated by two numerical examples.

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Acknowledgements

The authors would like to thank the editor and the anonymous reviewers for a number of valuable comments and constructive suggestions that have improved the quality of this paper. This work was supported by the Natural Science Foundation of Guangdong Province, China (Nos. 2016A030313005, 2015A030313643, and 2018A030313063).

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  1. School of Mathematics and Computational Science, Wuyi University, Jiangmen, 529020, Guangdong, China

    Kaizhong Guan & Jun Xi

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  1. Kaizhong Guan
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  2. Jun Xi
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Correspondence to Kaizhong Guan.

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Guan, K., Xi, J. A Novel Delay-Dependent Criterion for Global Power Stability of Cellular Neural Networks with Proportional Delay. Neural Process Lett 51, 867–880 (2020). https://doi.org/10.1007/s11063-019-10126-5

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