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The Intermittent Control Synchronization of Complex-Valued Memristive Recurrent Neural Networks with Time-Delays

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Abstract

In this paper, the intermittent control synchronization of complex-valued memristive recurrent neural networks with time-delays is investigated. As a generalization on the real-valued memristive recurrent neural networks, complex-valued memristive recurrent neural networks own more complicated properties. In complex-valued domain, bounded and analytic complex-valued activation functions do not exist. Some assumptions about activation functions in real-valued domain cannot be applied directly to complex-valued fields. By appropriate transformation, complex-valued memristive recurrent neural networks can be divided into real parts and imaginary parts, which can avoid discussing the bounded and analytic. In the framework of differential inclusion theory and Lyapunov method, sufficient criteria of intermittent control synchronization are established. Finally, a simulation is given to verify the validity and feasibility of the sufficient conditions.

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Authors and Affiliations

  1. School of Science, Jiangnan University, Wuxi, 214122, People’s Republic of China

    Yongqing Yang

  2. School of IoT Engineering, Jiangnan University, Wuxi, 214122, People’s Republic of China

    Shuai Zhang & Xin Sui

Authors
  1. Shuai Zhang
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  2. Yongqing Yang
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  3. Xin Sui
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Correspondence to Yongqing Yang.

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This work was jointly supported by the Natural Science Foundation of Jiangsu Province of China under Grant No. BK20161126, BK20170171, Postgraduate Research & Practice Innovation Program of Jiangsu Province under Grant Nos. KYCX18_1857, KYCX18_1858.

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Zhang, S., Yang, Y. & Sui, X. The Intermittent Control Synchronization of Complex-Valued Memristive Recurrent Neural Networks with Time-Delays. Neural Process Lett 50, 2119–2139 (2019). https://doi.org/10.1007/s11063-019-09988-6

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