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Description: 1、该工具箱包括了混沌时间序列分析与预测的常用方法,有:
(1)产生混沌时间序列(chaotic time series)
Logistic映射 - \ChaosAttractors\Main_Logistic.m
Henon映射 - \ChaosAttractors\Main_Henon.m
Lorenz吸引子 - \ChaosAttractors\Main_Lorenz.m
Duffing吸引子 - \ChaosAttractors\Main_Duffing.m
Duffing2吸引子 - \ChaosAttractors\Main_Duffing2.m
Rossler吸引子 - \ChaosAttractors\Main_Rossler.m
Chens吸引子 - \ChaosAttractors\Main_Chens.m
Ikeda吸引子 - \ChaosAttractors\Main_Ikeda.m
MackeyGLass序列 - \ChaosAttractors\Main_MackeyGLass.m
Quadratic序列 - \ChaosAttractors\Main_Quadratic.m
(2)求时延(delay time)
自相关法 - \DelayTime_Others\Main_AutoCorrelation.m
平均位移法 - \DelayTime_Others\Main_AverageDisplacement.m
(去偏)复自相关法 - \DelayTime_Others\Main_ComplexAutoCorrelation.m
互信息法 - \DelayTime_MutualInformation\Main_Mutual_Information.m
(3)求嵌入维(embedding dimension)
假近邻法 - \EmbeddingDimension_FNN\Main_FNN.m
Cao方法 - \EmbeddingDimension_Cao\Main_EmbeddingDimension_Cao.m
(4)同时求时延与嵌入窗(delay time & embedding window)
CC方法 - \C-C Method\Main_CC_Luzhenbo.m
(5)求关联维(correlation dimension)
GP算法 - \CorrelationDimension_GP\Main_CorrelationDimension_GP.m
(6)求K熵(Kolmogorov Entropy)
GP算法 - \KolmogorovEntropy_GP\Main_KolmogorovEntropy_GP.m
STB算法 - \KolmogorovEntropy_STB\Main_KolmogorovEntropy_STB.m
(7)求最大Lyapunov指数(largest Lyapunov exponent)
小数据量法 - \LargestLyapunov_Rosenstein\Main_LargestLyapunov_Rosenstein1.m
\LargestLyapunov_Rosenstein\Main_LargestLyapunov_Rosenstein2.m
\LargestLyapunov_Rosenstein\Main_LargestLyapunov_Rosenstein3.m
\LargestLyapunov_Rosenstein\Main_LargestLyapunov_Rosenstein4.m
(8)求Lyapunov指数谱(Lyapunov exponent spectrum)
BBA算法 -
\LyapunovSpectrum_BBA\Main_LyapunovSpectrum_BBA1.m
\LyapunovSpectrum_BBA\Main_LyapunovSpectrum_BBA2.m
(9)求二进制图形的盒子维(box dimension)和广义维(genealized dimension)
覆盖法 -
\BoxDimension_2D\Main_BoxDimension_2D.m
\GeneralizedDimension_2D\Main_GeneralizedDimension_2D.m
(10)求时间序列的盒子维(box dimension)和广义维(genealized dimension)
覆盖法 -
\BoxDimension_TS\Main_BoxDimension_TS.m
\GeneralizedDimension_TS\Main_GeneralizedDimension_TS.m
(11)混沌时间序列预测(chaotic time series prediction)
RBF神经网络一步预测 - \Prediction_RBF\Main_RBF.m
RBF神经网络多步预测 - \Prediction_RBF\Main_RBF_MultiStepPred.m
Volterra级数一步预测 - \Prediction_Volterra\Main_Volterra.m
Volterra级数多步预测 - \Prediction_Volterra\Main_Volterra_MultiStepPred.m
(12)产生替代数据(Surrogate Data)
随机相位法 - \SurrogateData\Main_SurrogateData.m
2、在matlab环境中首先运行install.m,将工具箱所在路径添加至matlab
3、各子目录下以Main_开头的文件即是主程序文件,直接按快捷键F5运行即可
4、工具箱中所有程序均在Matlab6.5和Matlab7.1环境中调试通过，不能保证在Matlab其它版本正确运行。
5、工具箱中部分功能为试用版，敬请谅解！
6、
作者：陆振波，海军工程大学
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