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Fixed-Time Synchronization of Neural Networks with Discrete Delay

Author

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  • Shuai Liu
  • Chuan Chen
  • Haipeng Peng

Abstract

In this paper, we establish a new fixed-time stability theorem, which provides a novel fixed-time stability criterion and a novel upper bound estimate formula for the settling time. Numerical simulations show that the upper bound estimate for the settling time in this paper is tighter than those given in the existing fixed-time stability theorems. By designing a simple feedback controller, the fixed-time synchronization of neural networks with discrete delay is investigated based on the fixed-time stability theorem established in this paper. A numerical example is included to validate the effectiveness of the obtained theoretical results.

Suggested Citation

  • Shuai Liu & Chuan Chen & Haipeng Peng, 2020. "Fixed-Time Synchronization of Neural Networks with Discrete Delay," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-9, August.
    • Handle: RePEc:hin:jnlmpe:7830547
    DOI: 10.1155/2020/7830547
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    Cited by:

    1. Wenqiang Yang & Li Xiao & Junjian Huang & Jinyue Yang, 2021. "Fixed-Time Synchronization of Neural Networks Based on Quantized Intermittent Control for Image Protection," Mathematics, MDPI, vol. 9(23), pages 1-14, November.
    2. Wu, Hongjuan & Li, Chuandong & He, Zhilong & Wang, Yinuo & He, Yingying, 2021. "Lag synchronization of nonlinear dynamical systems via asymmetric saturated impulsive control," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).

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