A complexity measure approach based on forbidden patterns and correlation degree  

作　　者：王福来 

机构地区：[1]Department of Mathematics and Statistics,Zhejiang University of Finance and Economics

出　　处：《Chinese Physics B》2010年第6期177-183,共7页中国物理B（英文版）

基　　金：Project supported by the National Natural Science Foundation of China (Grant No.10871168)

摘　　要：Based on forbidden patterns in symbolic dynamics, symbolic subsequences are classified and relations between forbidden patterns, correlation dimensions and complexity measures are studied. A complexity measure approach is proposed in order to separate deterministic （usually chaotic） series from random ones and measure the complexities of different dynamic systems. The complexity is related to the correlation dimensions, and the algorithm is simple and suitable for time series with noise. In the paper, the complexity measure method is used to study dynamic systems of the Logistic map and the Henon map with multi-parameters.Based on forbidden patterns in symbolic dynamics, symbolic subsequences are classified and relations between forbidden patterns, correlation dimensions and complexity measures are studied. A complexity measure approach is proposed in order to separate deterministic （usually chaotic） series from random ones and measure the complexities of different dynamic systems. The complexity is related to the correlation dimensions, and the algorithm is simple and suitable for time series with noise. In the paper, the complexity measure method is used to study dynamic systems of the Logistic map and the Henon map with multi-parameters.

关 键 词：complexity theory forbidden words symbolic dynamics correlation dimensions 

分 类 号：O211.61[理学—概率论与数理统计]