MATLAB-geometric-transformations

这是用来解常微分方程的原代码，是我自己编的哦。(This is the solution of ordinary differential equations for the original code, is a series of my own Oh.)

本代码是关于Multi-Dimensional Scaling（MDS）的代码，可以用于特征提取、特征选择，或是矩阵降维。(This file is part of the Matlab Toolbox for Dimensionality Reduction v0.4b. You are free to use, change, or However, )

可变块大小的方块编码源程序包括编码和解压两部分程序(Variable block size coding of the box including source code and extract the two parts of the procedure)

基于遗传算法的机器人路径规划算法matlab源代码(Genetic algorithm based path planning algorithm matlab source code)

说明：  matlab 程序，simulink 仿真，多自由度系统，源代码，求响应结果，分析。(the design about matlab,simulink)

hysys and matlab link3

Filename: Induction motor DQ0 model Description: This program illustrates DQ0 modelling of IM when it is operated with simple open loop variable voltage variable frequency strategy in Arbitrary Reference frame

在 Matlab/Simulink 中，建立独立的功能模块，如电机本体模块、矢量控制模块、速度控制模块、电流滞环控制模块等，再进行功能模块的有机整合，搭建交流异步电机控制系统的仿真模型。(In M atlab/Simulink, the independent function al blocks, such as Moter modelblock,Vector control block, Speed controller block, and Hysteresis current controllerblock etc,have been modeled. By the organic combination of these blocks, the model of control system canbe establishedeasily. )

双树复小波双变量阈值去噪，自己编写，仅供学习！(Tree complex wavelet bivariate threshold denoising, write your own, only to learn!)

克里金法广泛地应用于地下水模拟、土壤制图等领域，是一种很有用的地质统计格网化方法。它首先考虑的是空间属性在空间位置上的变异分布．确定对一个待插点值有影响的距离范围，然后用此范围内的采样点来估计待插点的属性值。该方法在数学上可对所研究的对象提供一种最佳线性无偏估计(某点处的确定值)的方法。它是考虑了信息样品的形状、大小及与待估计块段相互间的空间位置等几何特征以及品位的空间结构之后，为达到线性、无偏和最小估计方差的估计，而对每一个样品赋与一定的系数，最后　进行加权平均来估计块段品位的方法。(Kriging is a technique that provides the Best Linear Unbiased Estimator of the unknown fields (Journel and Huijbregts, 1978 Kitanidis, 1997). It is a local estimator that can provide the interpolation and extrapolation of the originally sparsely sampled data that are assumed to be reasonably characterized by the Intrinsic Statistical Model (ISM). An ISM does not require the quantity of interest to be stationary, i.e. its mean and standard deviation are independent of position, but rather that its covariance function depends on the separation of two data points)