Search - Embedding dimension

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[Other resource] EmbeddingDimension_FNN DL : 1: 假近邻法(False Nearest Neighbor, FNN)计算嵌入维的Matlab程序文件夹说明： Main_FNN.m - 程序主函数，直接运行此文件即可 LorenzData.dll - 产生Lorenz时间序列 PhaSpaRecon.m - 相空间重构 fnn_luzhenbo.dll - 假近邻计算主函数 SearchNN.dll - 近邻点搜索 buffer_SearchNN_1.dll - 近邻点搜索缓存1 buffer_SearchNN_2.dll - 近邻点搜索缓存2 参考文献： M.B.Kennel, R.Brown, H.D.I.Abarbanel. Determining embedding dimension for phase-space reconstruction using a geometrical construction[J]. Phys. Rev. A 1992,45:3403. -false neighbors (False Nearest Neighbor, FNN) calculation embedding dimension of the Matlab program folder : Main_FNN.m-procedure main function, Direct operating this document can be LorenzData.dll-time series produced Lorenz PhaS paRecon.m-phase space reconstruction fnn_luzhenbo.dll-calculated at the main function neighbors SearchNN.dll-point search buffer_SearchNN_1.dll neighbor - Search neighbor point a buffer_SearchNN_2.dll Cache-Cache Search neighbors point two reference Literature : M. B. Kennel, R. Brown, H. D. I. Abarbanel. Determining embedding dime nsion for phase-space reconstruction using a g eometrical construction [J]. Phys. Rev. A 1992 , 45:3403.
Update : 2008-10-13 Size : 97.68kb Publisher : 呆雁
[Other resource] bestdimensionm DL : 0: 在用混沌理论和神经网络进行短期负荷预测时，神经网络的输入的选择至关重要，该程序用matlabl实现了基于混沌时间序列的嵌入维数的选择-using chaos theory and neural networks for short-term load forecasts, the neural network is essential to choose an input, The procedure used matlabl achieved a chaotic time series based on the embedding dimension of choice
Update : 2008-10-13 Size : 1.2kb Publisher : sunyan
[WEB Code] Determining_embedding_dimension_for_phase-space_re DL : 0: 假近邻方法(False Nearest Neighbor,FNN)求混沌时间序列重构嵌入维-false neighbor approach (False Nearest Neighbor, FNN) for chaotic time series embedding dimension Reconstruction
Update : 2008-10-13 Size : 1.51mb Publisher : xujia
[Other] Determining_embedding_dimension_for_phase-space_re DL : 0: Determining embedding dimension for phase-space reconstruction using a geometrical construction. It is very important reference for time forecast in chaos sequence.
Update : 2008-10-13 Size : 1.5mb Publisher : 赵河
[Mathimatics-Numerical algorithms] 混沌时间序列预测 DL : 5: 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
Update : 2009-03-12 Size : 566.38kb Publisher : niuchao0511
[Documents] Determining_embedding_dimension_for_phase-space_re DL : 0: 假近邻方法(False Nearest Neighbor,FNN)求混沌时间序列重构嵌入维-false neighbor approach (False Nearest Neighbor, FNN) for chaotic time series embedding dimension Reconstruction
Update : 2025-04-04 Size : 1.51mb Publisher : xujia
[AI-NN-PR] mutual DL : 0: 关于混沌Tisean3.0嵌入维的计算程序，希望对大家有用-Chaos Tisean3.0 embedding dimension on the calculation procedure, in the hope that useful to everybody
Update : 2025-04-04 Size : 75kb Publisher : yy
[Other] Determining_embedding_dimension_for_phase-space_re DL : 0: Determining embedding dimension for phase-space reconstruction using a geometrical construction. It is very important reference for time forecast in chaos sequence. -Determining embedding dimension for phase-space reconstruction using a geometrical construction.It is very important reference for time forecast in chaos sequence.
Update : 2025-04-04 Size : 1.5mb Publisher : 赵河
[Embeded-SCM Develop] Cao_m DL : 0: 计算嵌入维程序，可以应用于很多的方面-Embedding dimension calculation procedure can be applied to many aspects of
Update : 2025-04-04 Size : 23kb Publisher : neng
[matlab] mutual_information DL : 0: 在相空间重构中，用互信息法求最小关联嵌入维-In phase space reconstruction, the use of mutual information method associated minimum embedding dimension
Update : 2025-04-04 Size : 4kb Publisher : 刘洋
[matlab] gp DL : 0: 混沌时间序列预测中用gp算法求借嵌入维和分形维。-Chaotic time series prediction by using gp algorithm for embedding dimension and fractal dimension.
Update : 2025-04-04 Size : 3kb Publisher : 章楷桦
[AI-NN-PR] Chaos_Prediction DL : 0: 混沌时间序列分析与预测源代码。具有产生混沌时间序列，求时延，求嵌入维，求关联维，求K熵，求Lyapunov指数谱，求二进制图形的盒子维和广义维，求时间序列的盒子维和广义维，混沌时间序列预测等项功能。-Chaotic time series analysis and prediction of the source code. Has generated chaotic time series, and delay, and embedding dimension, and correlation dimension, and K-entropy, and Lyapunov exponent spectra, and the binary graphics box peacekeeping generalized dimensions, and time series of box-dimensional and generalized dimension, chaotic time series prediction functions.
Update : 2025-04-04 Size : 566kb Publisher : 李志
[Mathimatics-Numerical algorithms] GP_Algorithm DL : 0: GP算法计算时间序列想空间重构的最佳嵌入维数和延迟时间-GP algorithm space reconstruction time series like the best embedding dimension and delay time
Update : 2025-04-04 Size : 1kb Publisher : 张艳艳
[matlab] ChaosToolbVer.2.0 DL : 0: 混沌工具箱 C-C方法计算时间延迟和嵌入维数混沌时间序列预测-Chaos Toolbox CC method to calculate time delay and embedding dimension of chaotic time series prediction
Update : 2025-04-04 Size : 14kb Publisher : 潘水洋
[matlab] G_P DL : 0: 混沌时间序列分析中的Ｇ－Ｐ方法，用来计算相空间重构用到的关联维和嵌入维数-Chaotic time series analysis of the G-P method, used to calculate the phase-space reconstruction using the correlation dimension and embedding dimension
Update : 2025-04-04 Size : 1kb Publisher : lishuhui
[Algorithm] CCmethod2 DL : 0: 应用改进的CC法求取时间延迟和嵌入维数，效果不错-The modified CC method to strike a time delay and embedding dimension, good results
Update : 2025-04-04 Size : 2kb Publisher : NOAH CHAN
[matlab] ChaosToolbox2p0_trial DL : 0: 混沌工具箱（matlab）: 产生混沌时间序列求时延(delay time) 求嵌入维(embedding dimension) 求关联维(correlation dimension) 等等.....
Update : 2025-04-04 Size : 565kb Publisher : wangyouyi
[matlab] 2010-02-05(C-C) DL : 0: C-C算法应用关联积分能够同时估计出时间延迟和嵌入维数，是相空间重构的前提。本程序通过C-C算法计算duffing方程产生的混沌时间序列的时间延迟和嵌入维数。-CC algorithm is used to simultaneously estimate the correlation integral time delay and embedding dimension, is a prerequisite for phase space reconstruction. This procedure CC algorithm duffing equation chaotic time series generated by the time delay and embedding dimension.
Update : 2025-04-04 Size : 47kb Publisher :
[AI-NN-PR] Adaptive-Embedding-Dimension DL : 0: 嵌入维数自适应最小二乘支持向量机状态时间序列预测方法 Condition Time Series Prediction Using Least Squares Support Vector Machine with Adaptive Embedding Dimension 针对航空发动机状态时间序列预测中嵌入维数难于有效选取的问题, 提出一种基于嵌入维数自适应最小二乘支持向量机( L SSVM ) 的预测方法。该方法将嵌入维数作为影响状态时间序列预测精度的重要参数, 以交叉验证误差为评价准则, 利用粒子群优化( P SO ) 进化搜索LSSV M 预测模型的最优超参数与嵌入维数, 同时通过矩阵变换原理提高交叉验证过程的计算效率, 并最终建立优化后的L SSVM 预测模型。航空发动机排气温度( EGT ) 预测实例表明, 该方法可自适应选取适用于状态时间序列预测的最优嵌入维数且预测精度高, 适用于航空发动机状态时间序列预测。- T o deal wit h the difficulty of selecting an appro pr iate embedding dimension for aeroeng ine co ndition time series predictio n, a metho d based o n least squar es suppo rt vecto r machine ( L SSVM ) with ada ptive em bedding dimension is pro po sed. I n the method, the embedding dimensio n is identified as a parameter that af fects the accuracy o f the aer oengine condition time series predictio n par ticle sw arm o ptimizat ion ( P SO) is ap plied to optimize the hyperpar ameter s and embedding dimension of the L SSV M pr edict ion model cro ssv alida tion is applied to evaluate the perfo rmance o f the L SSVM predictio n mo del and matr ix tr ansfo rm is applied to the L SSVM pr ediction model tr aining to accelerate the crossvalidation evaluation pro cess. Ex periments on an aeroengine ex haust g as t emperatur e ( EGT ) predictio n demonst rates that the metho d is hig hly effective in em bedding dimension selection. In compar ison w ith co nv
Update : 2025-04-04 Size : 334kb Publisher :
[matlab] Cao--dimension DL : 0: cao算法，可以确定嵌入维数，从而实现相空间重构-Cao algorithm, embedding dimension of time series can be determined, so as to realize the phase space reconstruction
Update : 2025-04-04 Size : 63kb Publisher : 黄刘军

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