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Chin. Phys. B, 2010, Vol. 19(5): 050505    DOI: 10.1088/1674-1056/19/5/050505
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An efficient method of distinguishing chaos from noise

Wei Heng-Dong(魏恒东)a), Li Li-Ping(李立萍)a), and Guo Jian-Xiu(郭建秀)b)
a School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China; b College of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
Abstract  It is an important problem in chaos theory whether an observed irregular signal is deterministic chaotic or stochastic. We propose an efficient method for distinguishing deterministic chaotic from stochastic time series for short scalar time series. We first investigate, with the increase of the embedding dimension, the changing trend of the distance between two points which stay close in phase space. And then, we obtain the differences between Gaussian white noise and deterministic chaotic time series underlying this method. Finally, numerical experiments are presented to testify the validity and robustness of the method. Simulation results indicate that our method can distinguish deterministic chaotic from stochastic time series effectively even when the data are short and contaminated.
Keywords:  phase space reconstruction      average false nearest neighbour      chaos detection  
Received:  16 February 2009      Revised:  25 November 2009      Accepted manuscript online: 
PACS:  05.45.Gg (Control of chaos, applications of chaos)  
  05.45.Xt (Synchronization; coupled oscillators)  
  02.30.Yy (Control theory)  

Cite this article: 

Wei Heng-Dong(魏恒东), Li Li-Ping(李立萍), and Guo Jian-Xiu(郭建秀) An efficient method of distinguishing chaos from noise 2010 Chin. Phys. B 19 050505

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