Complexity analyses of multi-wing chaotic systems

doi:10.1088/1674-1056/22/5/050506

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.

Keywords: complexity multi-wing chaotic system statistical complexity measure (SCM) spectral entropy (SE)

Received: 30 August 2012
Revised: 15 October 2012
Accepted manuscript online:

PACS:	05.45.Tp	(Time series analysis)
	05.45.-a	(Nonlinear dynamics and chaos)

Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 61161006 and 61073187).

Corresponding Authors: Sun Ke-Hui
E-mail: kehui@csu.edu.cn

Cite this article:

He Shao-Bo (贺少波), Sun Ke-Hui (孙克辉), Zhu Cong-Xu (朱从旭) Complexity analyses of multi-wing chaotic systems 2013 Chin. Phys. B 22 050506

[1]	Wang X Y and Gao Y F 2010 Commun. Nonlinear Sci. Numer. Simulat. 15 99
[2]	Llling L 2009 Int. J. Nonlinear Anal. Theory Meth. Appl. 71 2958
[3]	Zhang R X and Yang S P 2009 Chin. Phys. B 18 3295
[4]	Niu Y J, Wang X Y, Nian F Z and Wang M J 2010 Chin. Phys. B 19 120507
[5]	Lü J H, Murah K and Sinha S 2008 Phys. Lett. A 372 3234
[6]	Yu S M, Tang K S and Lu J H 2008 IEEE Trans. Circ. Syst. 11 1168
[7]	Carlos G and Roberto H 2010 Open Biomed. Eng. J. 4 223
[8]	Christophe C J and Gregory K B 2011 Clin. Neurophysiol. 123 658
[9]	Yu S M, Tang K S and Lü J H 2008 Int. J. Circ. Theory Appl. 38 243
[10]	Yu S M, Tang K S and Lü J H 2008 IEEE Int. Symp. Circ. Syst. 32 768
[11]	Kais B, Abdessattar C and Ahmed T 2011 Chaos Solition. Fract. 44 79
[12]	Elwakil A S and Özoguz S A 2008 Int. J. Bifurcat. Chaos 18 841
[13]	Giuseppe G, Frank L S and Damon A M 2009 Chaos Solition. Fract. 41 284
[14]	Higuchi T 1988 Physica D 31 277
[15]	Maragos P and Sun F K 1983 IEEE Trans. Signal Process. 41 108
[16]	Grassberger P and Procaccia I 1983 Phys. Rev. Lett. 50 346
[17]	Lempel A and Ziv J 1976 IEEE Trans. 22 75
[18]	Bant C and Pompe B 2002 Phys. Rev. Lett. 88 1741
[19]	Inoulye T, Shinosaki K and Sakamoto H 1991 Electroencephalogr. Clin. Neurophysiol. 79 204
[20]	Pincus S M 1995 Chaos 5 110
[21]	Richman J S and Moorman J R 2000 Am. J. Physiol. Heart Circ. Physiol. 278 2039
[22]	Phillip P A, Chiu F L and Nick S J 2009 Phys. Rev. E 79 011915
[23]	Zuino L, Zanin M and Tabak B M 2009 Physica A 388 2854
[24]	López-Ruiz R, Mancini H L and Calbet X 1995 Phys. Lett. A 209 321
[25]	Larrondo H A, González C M and Martin M T 2005 Physica A 356 133
[26]	Chen W T, Zhuang J and Yu W X 2009 Med. Eng. Phys. 31 61
[27]	Wolf A, Swift J and Swinney H 1985 Physica D 16 285

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