有限元计算程序，供软件工程，力学专业的老师和学生参考

遗传算法入门实例之一：用在PID参数整定上(转自阿莫论坛)

本代码是关于ldpc的编译码源代码，用的是c++语言，可以运行并且相关的矩阵文件都在附件里，可以通过这套程序来系统的学习通信的整个框架知识，希望能造福于后人

^ x = 140851752bruteforce x

类是将一个未知样本分到几个预先已知类的过程。 在众多的分类模型中，应用最为广泛的两种分类模型是决策树模型(Decision Tree Model)和朴素贝叶斯模型（Naive Bayesian Model，NBC）。

向来汉诺塔说的都是三个柱子的。。。。 那么四个柱子的呢？ 从三柱到四柱。。。。。熟练掌握递归-has said are the three pillars. . . . Then the four pillars? From the three- to four-post. . . . . Skilled master recursive.

TLD is an algorithm for tracking of unknown objects in unconstrained video streams. The object of interest is defined by a bounding box in a single frame. TLD simultaneously tracks the object, learns its appearance and detects it whenever it appears in the video. You are allowed to use TLD under the terms of the GPL version 3.0. It means that any distributed project that includes or links any portion of TLD source code has to be released with the source code under the GPL version 3.0 license or later. The details of the license can be found in file LICENSE. If you wish to use this code or any of its part for com

常微分方程的龙格库塔法系列程序，从二级到四级的算法。-Ordinary Differential Equations Runge- Kutta method series of procedures, from two to four algorithms.

此程序为2011年研究生数学建模试题的解答。程序中用到了Floyd算法，遗传算法，很好的解决了该问题。

PCA，也就是PrincipalComponents Analysis，主成份分析，是个很优秀的算法，其原理是寻找最小均方意义下，最能代表原始数据的投影方法然后自己的说法就是：主要用于特征的降维。另外，这个算法也有一个经典的应用：人脸识别。这里稍微扯一下，无非是把处理好的人脸图片的每一行凑一起作为特征向量，然后用PAC算法降维搞定之。

建立了一种基于移动最小二乘(Moving Least-Squares MLS)法的曲线曲 面拟合方法 这种方法对传统的最小二乘(LS)法的作了比较大的改进 使生成的曲线曲面具 有精度高 光滑性好等许多优点 详细介绍了移动最小二乘法的原理 应用和特点 并且给 出了使用移动最小二乘法进行曲线曲面拟合的程序设计流程 最后给出了曲线拟合和空间散 乱数据曲面拟合算例 将拟合结果与最小二乘拟合结果作了比较 分析了 MLS 拟合曲线曲 面的光滑性和拟合质量 表明了该方法的优越性和有效性-Was established based on moving least square (Moving Least-Squares MLS) method of this curve and surface fitting method to the traditional method of least squares (LS) method was relatively large improvements to make the generated curves and surfaces with a precision of High smoothness, good detail, and many other advantages of the principle of least-squares method for mobile applications and features and gives the least-squares method using the mobile curve and surface fitting procedure design process Finally, curve fitting and spatial scattered data surface to be cost-effective cases of the results of the fitting results are compared with the least-squares fitting analysis of MLS fitting curves and surfaces smooth and fitting quality demon