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Chinese Physics, 2005, Vol. 14(12): 2428-2432    DOI: 10.1088/1009-1963/14/12/010
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Detecting dynamical complexity changes in time series using the base-scale entropy

Li Jin (李锦)ab, Ning Xin-Bao (宁新宝)a, Wu Wei (吴巍)a, Ma Xiao-Fei (马小飞)a
a State Key Laboratory of Modern Acoustics, Institute for Biomedical Electronical Engineering, Nanjing University, Nanjing 210093, China; b College of Physics and Information Technology, Shaanxi Normal University, Xi'an 710062, China
Abstract  Timely detection of dynamical complexity changes in natural and man-made systems has deep scientific and practical meanings. We introduce a complexity measure for time series: the base-scale entropy. The definition directly applies to arbitrary real-word data. We illustrate our method on a practical speech signal and in a theoretical chaotic system. The results show that the simple and easily calculated measure of base-scale entropy can be effectively used to detect qualitative and quantitative dynamical changes.
Keywords:  dynamical complexity      the base-scale entropy      the zero-crossing rate      Lyapunov exponent  
Received:  10 May 2005      Revised:  16 June 2005      Accepted manuscript online: 
PACS:  05.45.Tp (Time series analysis)  
  43.72.Ar (Speech analysis and analysis techniques; parametric representation of speech)  

Cite this article: 

Li Jin (李锦), Ning Xin-Bao (宁新宝), Wu Wei (吴巍), Ma Xiao-Fei (马小飞) Detecting dynamical complexity changes in time series using the base-scale entropy 2005 Chinese Physics 14 2428

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