Neural Processing Letters

, Volume 50, Issue 3, pp 2183–2200 | Cite as

Global Exponential Synchronization of Delayed Complex-Valued Recurrent Neural Networks with Discontinuous Activations

  • Lian DuanEmail author
  • Min Shi
  • Zengyun Wang
  • Lihong Huang


In this paper, we are concerned with the exponential synchronization for a class of two delayed complex-valued recurrent neural networks (CVRNNs) with discontinuous neuron activations. By separating CVRNNs into real and imaginary parts, forming an equivalent real-valued subsystems, under the framework of differential inclusions, novel state feedback controllers are designed and novel criteria are established to ensure the exponential stability of error system, and thus the drive system exponentially synchronize with the response system. The obtained results are essentially new and complement previously known ones. The practicability of theoretical results is also supported via a numerical example.


Complex-valued neural network Exponential synchronization State feedback control 



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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Lian Duan
    • 1
    • 2
    Email author
  • Min Shi
    • 1
  • Zengyun Wang
    • 3
  • Lihong Huang
    • 4
  1. 1.School of Mathematics and Big DataAnhui University of Science and TechnologyHuainanPeople’s Republic of China
  2. 2.School of Mathematics and StatisticsCentral South UniversityChangshaPeople’s Republic of China
  3. 3.Department of MathematicsHunan First Normal UniversityChangshaPeople’s Republic of China
  4. 4.School of Mathematics and StatisticsChangsha University of Science and TechnologyChangshaPeople’s Republic of China

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