|本期目录/Table of Contents|

[1]张雨.混沌时间序列拟随机性的一种解释[J].南京工程学院学报(自科版),2017,15(02):52-55.[doi:10.13960/j.issn.1672-2558.2017.02.009]
 ZHANG Yu.An Explanation of Quasi-Randomness of Chaotic Time Series[J].Journal of Nanjing Institute of Technology(Natural Science Edition),2017,15(02):52-55.[doi:10.13960/j.issn.1672-2558.2017.02.009]
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《南京工程学院学报(自科版)》[ISSN:1672-2558/CN:SN32-1671/N]

卷:
第15卷
期数:
2017年02期
页码:
52-55
栏目:
出版日期:
2017-06-30

文章信息/Info

Title:
An Explanation of Quasi-Randomness of Chaotic Time Series
作者:
张雨
南京工程学院汽车与轨道交通学院, 江苏 南京 211167
Author(s):
ZHANG Yu
School of Automotive and Rail Transit, Nanjing Institute of Technology, Nanjing 211167, China
关键词:
动力系统分析 拟随机性 随机与混沌的关联性 时间序列特征 自功率谱密度函数 符号序列直方图 Shannon熵 重构相空间维数 符号序列长度
Keywords:
dynamic system analysis quasi-randomness relationship between random and chaos time series
分类号:
O19; O23
DOI:
10.13960/j.issn.1672-2558.2017.02.009
文献标志码:
A
摘要:
为“混沌时间序列具有拟随机性”的论点给出了时间序列方面的案例解释.采用自功率谱密度函数、符号序列直方图及其Shannon熵、重构相空间维数(符号序列长度)等几个时间序列特征,比较随机数据与混沌数据的差异.结果表明,对于自功率谱密度函数和符号序列直方图及其Shannon熵,随机数据与混沌数据之间特征相近.对于重构相空间维数(符号序列长度),随机数据与混沌数据之间特征有差异.故此,论证了混沌时间序列具有拟随机性的性质.
Abstract:
Some cases of time series are given to explain arguments about “chaotic time series being with quasi-randomness” in this paper. The difference between random data and chaotic data is compared by using some time series characteristics, including self-power spectral density function, symbol series histogram and Shannon entropy, reconstructed phase space dimension(symbol series length). The results show that there are similar features between random data and chaotic data when self-power spectral density function, symbol series histogram and Shannon entropy are applied. Meanwhile there are different features between random data and chaotic data when reconstructed phase space dimension(symbol series length)is applied. The nature of “chaotic time series being with quasi-randomness” is thus demonstrated.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2016-12-16
作者简介: 张雨,博士,教授,研究方向为车辆及其装备性能检测与控制.E-mail: zy586187@163.com
更新日期/Last Update: 2017-04-20