中国物理B ›› 2013, Vol. 22 ›› Issue (5): 50506-050506.doi: 10.1088/1674-1056/22/5/050506

• GENERAL • 上一篇    下一篇

Complexity analyses of multi-wing chaotic systems

贺少波, 孙克辉, 朱从旭   

  1. School of Physics and Electronics, Central South University, Changsha 410083, China
  • 收稿日期:2012-08-30 修回日期:2012-10-15 出版日期:2013-04-01 发布日期:2013-04-01
  • 基金资助:
    Project supported by the National Natural Science Foundation of China (Grant Nos. 61161006 and 61073187).

Complexity analyses of multi-wing chaotic systems

He Shao-Bo (贺少波), Sun Ke-Hui (孙克辉), Zhu Cong-Xu (朱从旭)   

  1. School of Physics and Electronics, Central South University, Changsha 410083, China
  • Received:2012-08-30 Revised:2012-10-15 Online:2013-04-01 Published:2013-04-01
  • Contact: Sun Ke-Hui E-mail:kehui@csu.edu.cn
  • Supported by:
    Project supported by the National Natural Science Foundation of China (Grant Nos. 61161006 and 61073187).

摘要: The complexities of multi-wing chaotic systems based on the modified Chen system and multi-segment quadratic function are investigated by employing statistical complexity measure (SCM) and spectral entropy (SE) algorithm. How to choose the parameters of the SCM and SE algorithms is discussed. The results show that the complexity of the multi-wing chaotic system does not increase as the number of wings increases, and it is consistent with the results of the Grassberger-Procaccia (GP) algorithm and the largest Lyapunov exponent (LLE) of the multi-wing chaotic system. This conclusion is verified by other multi-wing chaotic systems.

关键词: complexity, multi-wing chaotic system, statistical complexity measure (SCM), spectral entropy (SE)

Abstract: The complexities of multi-wing chaotic systems based on the modified Chen system and multi-segment quadratic function are investigated by employing statistical complexity measure (SCM) and spectral entropy (SE) algorithm. How to choose the parameters of the SCM and SE algorithms is discussed. The results show that the complexity of the multi-wing chaotic system does not increase as the number of wings increases, and it is consistent with the results of the Grassberger-Procaccia (GP) algorithm and the largest Lyapunov exponent (LLE) of the multi-wing chaotic system. This conclusion is verified by other multi-wing chaotic systems.

Key words: complexity, multi-wing chaotic system, statistical complexity measure (SCM), spectral entropy (SE)

中图分类号:  (Time series analysis)

  • 05.45.Tp
05.45.-a (Nonlinear dynamics and chaos)