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.
Received: 10 May 2005
Revised: 16 June 2005
Accepted manuscript online:
(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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