UMAT_Hashin3D

子空间学习方法工具箱，包含PCA、LDA、LLE、ISOMAP等经典子空间分析方法(Subspace learning method toolbox, including classical subspace analysis methods such as PCA, LDA, LLE, ISOMAP and so on)

说明：  利用四阶龙格库塔求解微分方程，并给出方程实例。(The fourth order Runge Kutta is used to solve the differential equation and an example is given.)

这是一个有关解二维弹性板的无网格EFG程序matlab源代码,是学习无网格法入门的必学程序!(This is a solution of two-dimensional elastic plate meshless EFG process matlab source code, is a meshless method to study entry procedures must!)

用Monte-Carlo方法解决二维Ising模型(Monte-Carlo method used to solve two-dimensional Ising model)

zero shift fitering to be used in offline system identification

2维非结构欧拉求解 fortran代码，用于2维流场求解(2D Unstructured Euler code)

最小二乘支持向量机做预测。程序可运行学习。在matlab上运行。(This is a program about prediction using LSSVM.It can run successfully for learning.This program can be used on matlab.)

采用时域数值仿真算法较为精确的仿真铣削加工过程动态力(By using numerical simulation algorithm is more accurate simulation of milling process dynamic force)

离散数据生成tin的优秀代码，注释多，易于学习和移植(Discrete data generated tin excellent code, comments, easy to learn and transplantation)

包括基本的克里金(Kriging)插值法实现代码，仅实现基本方法部分，不包含扩展克里金方法( kriging uses ordinary kriging to interpolate a variable z measured at locations with the coordinates x and y at unsampled locations xi, yi. The function requires the variable vstruct that contains all necessary information on the variogram. vstruct is the forth output argument of the function variogramfit. This is a rudimentary, but easy to use function to perform a simple kriging interpolation. I call it rudimentary since it always includes ALL observations to estimate values at unsampled locations. This may not be necessary when sample locations are not within the autocorrelation range but would require something like a k nearest neighbor search algorithm or something similar. Thus, the algorithms works best for relatively small numbers of observations (100-500). For larger numbers of observations I recommend the use of GSTAT. Note that kriging fails if there are two or more observa)