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Duffing_Cao.rar
- CAO方法求DUFFING方程的嵌入维数,CAO method DUFFING equation for embedding dimension
watermarkingweishue
- 运用和维数实现数字水印的嵌入、提取、与检测，实验结果不错-Dimension of the application and realization of digital watermark embedding, extraction, and test results good
2
- 相空间重构中嵌入维数和延迟时间的选择关系到非线性时间序列重构的质量，介绍了小波变换方法确定重构中的两个参数-Reconstruction of phase space embedding dimension and delay time related to the choice of the quality of reconstruction of nonlinear time series, introduces the wavelet transform method to determi
lle
- 局部线性嵌入，是一种流行学习的算法，可以学习任意维数的低维流形-locally linear embedding is a algorithm of manifold learning, it can be used to learn arbitrary dimension of low dimensional manifold
C_one
- 关联维数参数（嵌入维数和时间延迟）的计算 。读取txt波形数据，绘制图形，利用CC方法分析图形的的嵌入维数和时间延迟-The correlation dimension parameters (embedding dimension and time delay) calculation. Read txt waveform data, draw pictures using the CC method to analyze the graph of the embedding dimensio
C_CMethod
- 利用这个方法计算混沌时间序列的时间延迟和嵌入维数-Time delay and embedding dimension of chaotic time series calculated using this method
cnn
- 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-Chaos theory and neural network short-term load forecasting, neural network input is essential to choose the program implemented in matlabl choice of embedding dimension based on chaot
LEM-Algorithm
- LEM（拉普拉斯特征映射）算法，拉普拉斯特征映射是基于局部邻域，保持局部结构的流形学习方法。LEM通过一个无向加权图刻画流形上数据点间的近邻关系，图的顶点为原始数据点，图的边对应点之间的近邻关系，边的权值对应近邻点之间的相似程度（也可以是某种距离），LEM在低维嵌入空间中尽量保持图中数据点之间的近邻关系，然后求取嵌入坐标。通俗的说，LEM认为在高维数据空间离得近的点在低维嵌入空间也应该离得近-LEM (Laplace feature mapping) algorithm, Laplace fea
sitay_calculating
- C-C方法计算时间延迟和嵌入维数计算Lyapunov指数计算关联维数混沌时间序列预测,(C - C time delay and embedding dimension method to calculate the Lyapunov index calculating correlation dimension chaotic time series prediction,)