<DIV >混沌时间序列分析与预测工具箱 Version1.0<BR>chaotic time series analysis and prediction matlab toolbox - version 1.0<BR><BR>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:<BR><BR>(1)产生混沌时间序列(chaotic time series)<BR>Logistic映射 - \ChaosAttractors\Main_Logistic.m<BR>Henon映射 - \ChaosAttractors\Main_Henon.m<BR>Lorenz吸引子 - \ChaosAttractors\Main_Lorenz.m<BR>Duffing吸引子 - \ChaosAttractors\Main_Duffing.m<BR>Duffing2吸引子 - \ChaosAttractors\Main_Duffing2.m<BR>Rossler吸引子 - \ChaosAttractors\Main_Rossler.m<BR>Chens吸引子 - \ChaosAttractors\Main_Chens.m<BR><BR>(2)求时延的(delay time)<BR>自相关法 - \DelayTime_Others\Main_AutoCorrelation.m<BR>平均位移法 - \DelayTime_Others\Main_AverageDisplacement.m<BR>(去偏)复自相关法 - \DelayTime_Others\Main_ComplexAutoCorrelation.m<BR>互信息法 - \DelayTime_MutualInformation\Main_Mutual_Information.m<BR><BR>(3)求嵌入维的(embedding dimension)<BR>假近邻法 - \EmbeddingDimension_FNN\Main_FNN.m<BR>Cao方法 - \EmbeddingDimension_Cao\Main_EmbeddingDimension_Cao.m<BR><BR>(4)同时求时延与嵌入窗的(delay time &amp; embedding window)<BR>CC方法 - \C-C Method\Main_CC_Luzhenbo.m<BR><BR>(5)求关联维的(correlation dimension)<BR>G-P算法 - \CorrelationDimension_GP\Main_GP_Algorithm.m<BR>Tackens算法 - \CorrelationDimension_Takens\Main_CorrelationDimension.m<BR><BR>(6)求最大Lyapunov指数的(largest Lyapunov exponent)<BR>小数据量法 - \LargestLyapunov_Rosenstein\Main_LargestLyapunov_Rosenstein1.m<BR> - \LargestLyapunov_Rosenstein\Main_LargestLyapunov_Rosenstein2.m<BR><BR>(7)混沌时间序列预测(chaotic time series prediction)<BR>RBF神经网络一步预测 - \Prediction_RBF\Main_RBF.m<BR>RBF神经网络多步预测 - \Prediction_RBF\Main_RBF_MultiStepPred.m<BR>Volterra级数一步预测 - \Prediction_Volterra\Main_Volterra.m<BR>Volterra级数多步预测 - \Prediction_Volterra\Main_Volterra_MultiStepPred.m<BR><BR>2、在matlab环境中首先运行install.m,将工具箱所在路径添加至matlab<BR><BR>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<BR><BR>4、工具箱中部分功能为试用版，敬请谅解！</DIV><BR>