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[Other resource] Prediction_Volterra

Description: 混沌时间序列预测(chaotic time series prediction)中的Volterra级数一步预测 、Volterra级数多步预测方法
Platform: | Size: 12621 | Author: 李洁 | Hits:

[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:

[matlab] Prediction_Volterra

Description: 混沌时间序列预测(chaotic time series prediction)中的Volterra级数一步预测 、Volterra级数多步预测方法-Prediction of chaotic time series (chaotic time series prediction) in the prediction step Volterra series, Volterra series multi-step prediction method
Platform: | Size: 12288 | Author: 李洁 | Hits:

[Books] Prediction_Volterra

Description:
Platform: | Size: 15360 | Author: chenchen | Hits:

[matlab] Prediction_Volterra

Description: 混沌时间序列预测-Volterra级数一步及多步预测-Progression step and multi-step prediction of chaotic time series prediction-Volterra
Platform: | Size: 15360 | Author: 孙扬 | Hits:

[Windows Develop] Prediction_RBF

Description: 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-Chaotic Time Series Prediction (chaotic time series prediction) RBF neural network prediction step- \ Prediction_RBF \ Main_RBF.m RBF Neural Network Multi- Step Prediction- \ Prediction_RBF \ Main_RBF_MultiStepPred.m Volterra series step prediction- \ Prediction_Volterra \ Main_Volterra.m Volterra level the number of multi-step prediction- \ Prediction_Volterra \ Main_Volterra_MultiStepPred.m
Platform: | Size: 776192 | Author: houguoq | Hits:

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