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中国物理学会期刊

基于相空间邻域的混沌时间序列自适应预测滤波器(Ⅱ)非线性自适应滤波

CSTR: 32037.14.aps.52.1102

Adaptive predict-filter of chaotic time series constructed Based on the neighbou rhood in the reconstructed phase space(Ⅱ)nonlinear adaptive filter

CSTR: 32037.14.aps.52.1102
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  • 根据相空间重构理论、最小均方误差准则和最陡下降原理,提出了一种基于相空间邻域的非线性自适应滤波算法.实验结果表明:这种非线性自适应预测滤波器能够有效预测一些混沌序列,在某种程度上具有抗噪声的能力.

     

    A kind of adaptive nonlinear predict-filter of chaotic time series using the neighbourhood in the reconstructed phase space,the minimum square-root-error criterion and the steepest descent principle is proposed.It can convert the time domain into the multi-dimensional vector domain, and predict chaotic time series by nonlinear filter. The result of computer simulation illustrates that the algorithm is available to predict some chaotic series and anti-noise.

     

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