Open AccessComplexity analysis of chaotic sequence based on the intensive statistical complexity algorithm
Author(s) -
Kehui Sun,
Shaobo He,
Sheng Li-Yuan
Publication year - 2011
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.60.020505
Subject(s) - chaotic , algorithm , sequence (biology) , computer science , encryption , computational complexity theory , series (stratigraphy) , pseudorandom number generator , theoretical computer science , mathematics , statistical physics , artificial intelligence , physics , paleontology , genetics , biology , operating system
To analyze the complexity of the chaotic sequences, based on the intensive statistical complexity algorithm, the complexities of the discrete TD-ERCS and continuous simplified Lorenz chaotic systems were investigated respectively, and the complexities of the chaotic sequences with different system parameters were calculated. The complexities of pseudo-random sequences of the continuous chaotic systems disordered by m-series and chaotic pseudo-random sequences were analyzed. The results indicate that the intensive statistical complexity algorithm is an effective method for analyzing the complexity of the chaotic sequences, and the complexity of the discrete chaotic systems is larger than that of the continuous ones. However, after disordering by m-series or chaotic pseudo-random sequences, the complexities of the pseudo-random sequences can be increased significantly. This study provides a theoretical basis for the applications of chaotic sequences in the field of secure communication and information encryption.