KPCA故障检测

m_map包，用于绘制地图，很好用的一个matlab绘图工具包(m_map this can help you draw a map with the matlab this can make you to draw a map)

将数据集转换为拉普拉斯矩阵，然后利用基于图论的谱聚类进行聚类。拉普拉斯矩阵采用高斯核函数，全连接方法计算。谱聚类擅长处理高维数据或非凸数据集。(The data set is transformed into Laplacian matrix, and then clustered by spectral clustering based on graph theory. The Laplacian matrix is calculated by using the Gauss kernel function and the full connection method. Spectral clustering is good at dealing with high-dimensional or non-convex data sets.)

说明：  多种基本分类训练，包括支持向量机，偏最小二乘，主成分分析和线性分析(A variety of basic classification training, including support vector machine, partial least squares, principal component analysis and linear analysis)

用最小二乘法计算分形图案的维数,试试看怎么样,请多包涵！！(Use the least square method to calculate the dimensions of fractal patterns, try how, please include more!)

一种特征提取方法：结合主元分析(PCA)和核主元分析（KPCA）的前馈神经网络（FNN）(A feature extraction method: the feedforward neural network (FNN) combined with principal component analysis (PCA) and kernel principal component analysis (KPCA))

数组排序,按照数组的某个元素进行排序,使用请查看(Sort the array, in accordance with a certain element of the array to sort, the use of please see)

floyd，求最短路径的算法。。求任意两点间的最短距离(floyd, seeking the shortest path algorithms. . Arbitrary order of the shortest distance between two points)

通过k均值算法寻找类中心，聚类，对数据实现有效划分。(The k-means algorithm is used to find the class center, the data is clustered and the data is divided.)

粒子群优化SVM参数 遗传算法优化SVM参数(Particle Swarm Optimization of SVM Parameters)

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)