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[Mathimatics-Numerical algorithms] 混沌时间序列预测

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 欢迎同行来信交流与合作，更多文章与程序下载请访问我的个人主页
Platform: | Size: 579972 | Author: niuchao0511 | Hits:

[Other] lyapunov+expon

Description: 混沌Chaos工具箱，计算Lyapunov指数非常准确。-Chaos Chaos toolbox for calculating Lyapunov index very accurate.
Platform: | Size: 3072 | Author: aujjww | Hits:

[matlab] lyapunov

Description: 混沌系统lypunov指数谱，rucklidge系统指数-Chaotic system lypunov index spectrum, rucklidge system index
Platform: | Size: 1024 | Author: 张兵 | Hits:

[matlab] annlyap

Description: 最小RMSE神经网络方法计算Lyapunov指数的matlab函数。-This M-file calculates Lyapunov exponents with minimum RMSE neural network. After estimation of network weights and finding network with minimum BIC, derivatives are calculated. Sum of logarithm of QR decomposition on Jacobian matrix for observations gives spectrum of Lyapunov Exponents. Using the code is very simple, it needs only an scalar time series, number of lags and number of hidden unites. Higher number of hidden units leads to more precise estimation of Lyapunov exponent, but it is time consuming for less powerful personal computers. Number of lags determines number of embedding dimensions. Therefore, please give number of lags equal to number of embedding dimension. The codes creates networks with various neurons up to user supplied value for neurons and lags up to user specified number lags. Total number of networks are equal to number of neurons times number of lags. this modeling strategy is complex but helps to user select embedding dimension based on minimum BIC.
Platform: | Size: 2048 | Author: miaomiao | Hits:

[Other] mangtui

Description: 基于互功率谱的时延估计，混沌的判断指标Lyapunov指数计算,使用matlab实现智能预测控制算法。- Based on the time delay estimation of power spectrum, Chaos indicator for Lyapunov index calculation, Use matlab intelligent predictive control algorithm.
Platform: | Size: 5120 | Author: ugaemaf | Hits:

[matlab] geikang

Description: 旋转机械二维全息谱计算的实用例程，wolf 方法计算李雅普诺夫指数,用MATLAB实现的压缩传感。- Rotating Machinery dimensional hologram of practical spectrum calculation routines, wolf calculated Lyapunov exponent, Using MATLAB compressed sensing.
Platform: | Size: 5120 | Author: 张美安 | Hits:

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