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pmf
- 推荐系统 概率矩阵分解代码 内部已包含有数据集，已分为训练集与测试集-Recommended system probability matrix decomposition Code
NMF
- 用matlab实现的基于非负矩阵分解NMF的聚类算法，已测试通过-NMF decomposition using clustering algorithm based on non-negative matrix matlab achieved, have been tested
extrema
- 解决EMD分解后端点不正确的现象，该算法能有效解决这一问题-EMD decomposition procedure to solve the problem endpoint, can effectively solve the endpoint of decomposition phenomenon incorrect
KSVD
- ELAD论文中的KSVD分解标准程序，可对照论文进行理解-ELAD papers in the KSVD decomposition standard procedures, can be controlled to understand the paper
SVD_EST
- 自行编写的加入噪声估计的KSVD去噪算法，利用SVD分解进行噪声估计- KSVD denoising algorithm to prepare the addition of noise estimation, the use of SVD decomposition noise estimation
cf_matrix-decomposition
- 现在比较常用的一种给予举证分解的协同过滤算法，用于个性化推荐-Now more commonly used as a collaborative filtering algorithm decomposition give evidence for personalized recommendation
svd
- 奇异值分解在某些方面与对称矩阵或厄米矩阵基于特征向量的对角化类似。然而这两种矩阵分解尽管有其相关性，但还是有明显的不同。-Singular value decomposition in some respects symmetric matrix or Hermitian matrix based on a similar feature vectors diagonalization. However, the two matrix decomposition in spite of its
Wind-Speed-Combined-Prediction
- 针对风电场短期风速的预测提出一种基于小波变换的组合预测方法。首先利用Mallat 算法对短期风速时间序列进行db3 小波三层分解与重构，得到短期风速时间序列的近似分量和细节分量。针对近似分量和细节分量的不同特性，对近似分量利用粒子群算法优化的最小二乘支持向量机进行预测，对细节分量利用自回归求和滑动平均模型进行预测。最后各预测模型预测值组合叠加得到最终的短期风速预测值。仿真结果表明该方法具有较高的预测准确度。-In order to improve short-term wind speed pr
Wavelet-Packet
- 基于混合信号的小波包分解技术在故障特征提取中的应用-Feature Extraction Using Multisignal Wavelet Packet Decomposition
SVD.m
- 利用SVD实现item-based CF: 优点： 简化数据，去除噪声，提高算法的结果 缺点： 数据的转换可能难以理解 适用数据类型： 数值型数据(Svd decomposition plays an important role in the decomposition of eigenvalues of high-dimensional data, while using low-dimensional data for approximate approximation)
emd1d
- 用python写的EMD分解，可以实现一维与二维分解(EMD decomposition written in Python)