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A New Complex Hyper-chaotic System and Chaotic Synchronization of Error Feedback with Disturbance

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Advances in Neural Networks – ISNN 2019 (ISNN 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11554))

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Abstract

In this paper, a new complex hyper-chaotic system is proposed. Through the separation of real and imaginary parts, the basic dynamics such as symmetry, dissipation, equilibrium stability, Lyapunov exponent spectrum and power spectrum are studied. Then, according to the Lyapunov stability theory, using the error feedback synchronization method, we design a complex feedback controller to realize the chaotic synchronization of the proposed chaotic system with both parameters and external disturbances. Theoretical analysis shows that the controller can make the synchronization error gradually towards zero point. In addition, the numerical simulation of the complex chaotic synchronization system is carried out. The simulation results further verify the effectiveness of the proposed method.

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Authors and Affiliations

  1. Southwest University, Chongqing, 400715, China

    Weidong Guan, Dengwei Yan, Lidan Wang & Shukai Duan

  2. Chongqing Key Laboratory of Brain Inspired Computing and Intelligent Control, Chongqing, 400715, China

    Weidong Guan, Dengwei Yan, Lidan Wang & Shukai Duan

  3. National and Local Joint Engineering Laboratory of Intelligent Transmission and Control Technology, Chongqing, 400715, China

    Weidong Guan, Dengwei Yan, Lidan Wang & Shukai Duan

Authors
  1. Weidong Guan
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  2. Dengwei Yan
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  3. Lidan Wang
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  4. Shukai Duan
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Corresponding author

Correspondence to Lidan Wang .

Editor information

Editors and Affiliations

  1. Dalian University of Technology, Dalian, China

    Huchuan Lu

  2. Sichuan University, Chengdu, China

    Huajin Tang

  3. Northeastern University, Shenyang, China

    Zhanshan Wang

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Guan, W., Yan, D., Wang, L., Duan, S. (2019). A New Complex Hyper-chaotic System and Chaotic Synchronization of Error Feedback with Disturbance. In: Lu, H., Tang, H., Wang, Z. (eds) Advances in Neural Networks – ISNN 2019. ISNN 2019. Lecture Notes in Computer Science(), vol 11554. Springer, Cham. https://doi.org/10.1007/978-3-030-22796-8_31

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  • DOI: https://doi.org/10.1007/978-3-030-22796-8_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-22795-1

  • Online ISBN: 978-3-030-22796-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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