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Exponential Synchronization of Neural Networks via Feedback Control in Complex Environment

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  • Xiaoxiao Lv
  • Xiaodi Li
  • Jinde Cao
  • Peiyong Duan

Abstract

The problem of exponential synchronization for neural networks is investigated via feedback control in complex environment. By constructing suitable Lyapunov-Krasovskii functionals and applying the piecewise analytic method, some sufficient criteria for exponential synchronization of the addressed neural networks are established in terms of linear matrix inequalities (LMIs). The feedback control in complex environment includes the delayed aperiodically intermittent control and dynamic output feedback control. Moreover, the delayed aperiodically intermittent dynamic output feedback controller is designed based on the established LMIs. A numerical example and its numerical simulations are finally presented to show the effectiveness of obtained theoretical results.

Suggested Citation

  • Xiaoxiao Lv & Xiaodi Li & Jinde Cao & Peiyong Duan, 2018. "Exponential Synchronization of Neural Networks via Feedback Control in Complex Environment," Complexity, Hindawi, vol. 2018, pages 1-13, July.
    • Handle: RePEc:hin:complx:4352714
    DOI: 10.1155/2018/4352714
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    Cited by:

    1. Yadav, Vijay K. & Shukla, Vijay K. & Das, Subir, 2021. "Exponential synchronization of fractional-order complex chaotic systems and its application," Chaos, Solitons & Fractals, Elsevier, vol. 147(C).
    2. Liu, Huixia & Lu, Lulu & Zhu, Yuan & Wei, Zhouchao & Yi, Ming, 2022. "Stochastic resonance: The response to envelope modulation signal for neural networks with different topologies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).

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