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中国物理学会期刊

基于最大Lyapunov指数的多变量混沌时间序列预测

CSTR: 32037.14.aps.58.756

Predication of multivariable chaotic time series based on maximal Lyapunov exponent

CSTR: 32037.14.aps.58.756
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  • 参考基于最大Lyapunov指数的单变量混沌时间序列预测方法,提出一种通过选取多个邻近重构向量,预测多变量混沌时间序列的局域法.采用新方法对两个完全不同的Rssler方程的耦合系统,Rssler方程和Hyper Rssler方程的耦合系统的多变量混沌时序进行一步和多步预测,结果表明了该方法的有效性,且算法具有较强的抗噪能力.讨论了参考邻近点数和预测结果的关系.

     

    A method for prediction of multivariable chaotic time series through selecting many neighboring reconstructed vectors is proposed with reference to the method for prediction of single-variable chaotic time series based on maximal Lyapunov exponent. The new method is used to forecast the chaotic time series of two Rssler equations coupled system, Rssler equation and Hyper Rssler equations coupled system for onestep and multistep. Results show that the algorithm can forecast multivariable chaotic time series precisely and has strong anti-chirp ability. The relation between the result and the number of neighbor points is discussed.

     

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