Matlab_VC

如何在vc6中调用matlab引擎进行科学计算。 包括，初始化引擎，数据交换等。(How to call matlab engine vc6 for scientific computing. Include engine initialization, data exchange, etc..)

本文着重描述了运用MATLAB命令将M文件翻译为C语言程序，并修改为可直接调用的C语言函数的方法，(This paper describes the use of MATLAB command M-file translation for the C language program, and modify the method can directly call C language functions)

主成分分析的代码，很有用，效果很好。这是一个比较有用的C++代码。(Principal component analysis of the code, very useful, very good. This is a more useful C++ code.)

图像模板匹配算法用MATLAB来试验，有例子大家可以看看，有上占还不完好，有能力的自己改改(Image template matching algorithm using MATLAB to test, there are examples we can see, there are not well accounted for, the ability of their changed)

matlab6.5图形图像处理源程序 matlab6.5图形图像处理源程序(matlab6.5 graphics images graphical treatment matlab6.5 source image processing source code)

感应双馈发电机系统的仿真，基于欧几里得距离的聚类分析，粒子图像分割及匹配均为自行编制的子例程。( Simulation of doubly fed induction generator system, Clustering analysis based on Euclidean distance, Particle image segmentation and matching subroutines themselves are prepared.)

关于电磁场中用超松弛法求网格电位位的matlab源代码 (Overrelaxation method using electromagnetic fields demand grid potential bit matlab source code)

How to start or stop a windows NT service.

对浮点型数据进行压缩，将数据分为3个部分：符号位、指数、尾数，分别对其进行压缩(Of floating-point type data compression, data is divided into three parts: sign bit, index, mantissa, respectively, to compress their)

梯度下降法是最早最简单，也是最为常用的最优化方法。梯度下降法实现简单，当目标函数是凸函数时，梯度下降法的解是全局解。一般情况下，其解不保证是全局最优解，梯度下降法的速度也未必是最快的。梯度下降法的优化思想是用当前位置负梯度方向作为搜索方向，因为该方向为当前位置的最快下降方向，所以也被称为是”最速下降法“。最速下降法越接近目标值，步长越小，前进越慢。(The gradient descent method is the earliest and most simple and most commonly used optimization method. The gradient descent method is simple to realize. When the objective function is a convex function, the solution of the gradient descent method is a global solution. In general, the solution is not guaranteed to be the global optimal solution, and the gradient descent method is not necessarily the fastest. The optimization idea of gradient descent method is to use the current position negative gradient direction as the search direction, because the direction is the fastest descending direction of the current position, so it is also called the steepest descent method. The faster the slowest descent approach is closer to the target, the smaller the step, the slower the progress.)