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Finite-Time Lag Synchronization for Memristive Mixed Delays Neural Networks with Parameter Mismatch

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Abstract

This paper is devoted to study the finite time lag synchronization problem of memristive mixed delays neural networks with switching jumps and parameter mismatch. The main objective of this paper is to design simple linear feedback control such as the drive response systems can realize synchronization in the finite time. Several theoretical aspects are addressed, mean Filippov differential inclusion and set-valued map. Based on the Gronwall’s inequality and properties of differential operation, a new finite time lag synchronization scheme is proposed to guarantee that coupled memristive mixed delays neural networks are in a state of lag synchronization in finite time. In addition, finite lag synchronization criteria of two identical memristive mixed delays neural networks are also considered. Finally, numerical examples are presented to illustrate the effectiveness of the our proposed theorems.

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Authors and Affiliations

  1. School of Science, Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi, 214122, People’s Republic of China

    Lingzhong Zhang, Yongqing Yang, Fei Wang & Xin Sui

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  1. Lingzhong Zhang
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  2. Yongqing Yang
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  3. Fei Wang
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  4. Xin Sui
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Corresponding author

Correspondence to Yongqing Yang.

Additional information

This work was jointly supported by the National Natural Science Foundation of Jiangsu Province of China under Grant No. BK20161126 and the Graduate Innovation Project of Jiangsu Province under Grant No. KYLX16\(_{-}\)0778.

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Zhang, L., Yang, Y., Wang, F. et al. Finite-Time Lag Synchronization for Memristive Mixed Delays Neural Networks with Parameter Mismatch. Neural Process Lett 47, 365–389 (2018). https://doi.org/10.1007/s11063-017-9653-z

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