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Lag quasi-synchronization for memristive neural networks with switching jumps mismatch

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Abstract

This paper is concerned with the lag quasi-synchronization for memristive neural networks (MNNs) with switching jumps mismatch. The inherent characteristic of MNNs is fully taken into account. Based on Lyapunov–Krasovskii functional and differential inclusions theory, intermittent control approach is utilized to realize the exponential lag quasi-synchronization of the considered model. The error level is closely related to the switching jumps. In addition, a simple design procedure of controller is presented to ensure that the synchronization error between the master system and the slave system converges to a predetermined level. Two numerical examples are offered to show the effectiveness of the proposed method.

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Acknowledgments

Foundation This work was supported by the National Natural Science Foundation of China (Grant Nos. 61473070, 61433004), the Fundamental Research Funds for the Central Universities (Grant Nos. N130504002, N150406003, and N130104001) and SAPI Fundamental Research Funds (Grant No. 2013ZCX01).

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  1. School of Information Science and Engineering, Northeastern University, Shenyang, 110819, China

    Sanbo Ding & Zhanshan Wang

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  1. Sanbo Ding
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  2. Zhanshan Wang
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Correspondence to Zhanshan Wang.

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Ding, S., Wang, Z. Lag quasi-synchronization for memristive neural networks with switching jumps mismatch. Neural Comput & Applic 28, 4011–4022 (2017). https://doi.org/10.1007/s00521-016-2291-y

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