一种利用小波包分析计算混沌时间序列Kolmogorov熵的方法
A Method of Computing Kolmogorov Entropy of the Chaotic Time Series with Wavelet Packet Analysis
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摘要: 提出了一种利用非线性时间序列的小波包变换模数代替混沌信号本身，在m维相空间中计算其Kolmogorov熵的方法，并用具体实例进行了仿真验算和噪声分析．结果表明，这种算法准确、可靠，并且可以有效克服采样过程中常常出现的噪声对信号的干扰．Abstract: In this paper, it is presented that Kolmogorov entropy of the chaotic signal can be computed inm-dimensional phase space with the wavelet packet transform modulus of the nonlinear time series instead of the chaotic signal itself. Based on simulation testing and noise analysis with some examples, it is found that this method is accurate and reliable. It can also overcome the noise disturbance to the signal during the sampling process.
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