很有用的算法哦。这是我好不容易找道的

学习CFD的基础教程，含有各种差分格式和高精度本质无振荡算法源程序。-learning CFD based directory containing a variety of formats and high-precision differential nature without oscillation algorithm source.

对于无约束问题，给出的共轭梯度法，内涵多个函数实例-For the unconstrained problem, given by the conjugate gradient method, the connotation of a number of examples of function

AString给出;问题是使用哈夫曼编码的字符串编码(分配比特根据频率ofcharacter每个字符的字符串),然后解码编码的字符串使用前缀免费代码。Apre fix 代码可以很容易地由一个二叉树表示。每个字符的编码是由以下外部节点的路径从theroot认为性格:0位标识左分支路径,和1位标识一个右分支。

LabVIEW implementation of neural net with 2 layers. Back Error Propagation learning example.

原题为： 1．有5栋5种颜色的房子 2．每一位房子的主人国籍都不同 3．这五个人每人只喝一个牌子的饮料，只抽一个牌子的香烟，只养一种宠物 4．没有人有相同的宠物，抽相同牌子的烟，喝相同牌子的饮料 已知条件： 1．英国人住在红房子里 2．瑞典人养了一条狗 3．丹麦人喝茶 4．绿房子在白房子的左边 5．绿房子主人喝咖啡 6．抽pallmall烟的人养了一只鸟 7．黄房子主人抽dunhill烟 8．住在中间房子的人喝牛奶 9．挪威人住在第一间房子 10．抽混合烟的人住在养猫人的旁边 11．养马人住在抽dunhill烟人的旁边 12．抽bluemaster烟的人喝啤酒 13．德国人抽prince烟 14．挪威人住在蓝房子旁边 15．抽混合烟的人的邻居喝矿泉水 问题：谁养鱼？ 这道迷题出自1981年柏林的德国逻辑思考学院。 据说世界上只有2％的人能出答案。 就连大名鼎鼎的爱因斯坦也成为此题大伤脑筋。-original entitled : 1. Have five five colors of the two houses. Each a master of the house three different nationality. Each of these five individuals only drink one brand of beverages, just the one brand of cigarettes, only raised a pet 4. No one has the same pet, and pumping the same brand of cigarettes, drink the same brand of beverages known conditions : 1. Britons living in Red House Lane 2. Swede custody of a dog 3. Denmark tea 4. Green house at the White house left five. Green coffee house owner 6. Pallmall pumpin

PID算法，名字没用PID,电机PID算法。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。。

C语言实现雨滴模拟，一个完整的过程分解为好几个小部分，各自可以独立运行，方便初学者学习c语言实现较为复杂的数据结构。

傅立叶变化，演示源码，可以很快入门，很好的小东西-Fourier changes demo source can be quickly entry, the small things well

逐次超松驰迭代法(Successive Over Relaxation Me thod,简称SOR方法)是高斯―塞德尔方法的一种加速方法，是解大型稀疏矩阵方程组的有效方法之一，它具有计算公式简单，程序设计容易,占用计算机内存较少等优点,但需要较好的加速因子(即最佳松驰因子).下面我们首先说说松驰一词的含意,再利用它来解释雅可比迭代法与高斯―塞德尔迭代法,最后给出逐次超松驰迭代法的推算公式和收敛性条件.-Successive over relaxation iteration method (Successive Over Relaxation Me thod, called SOR method) is the Gauss- Seidel method for an accelerated method is solution of large sparse matrix equations, one effective method, it has a simple formula, programming easy, take up less computer memory, etc., but the need for better acceleration factor (that is, the best relaxation factor). Let us first talk about the meaning of the term relaxation, and then use it to explain the Jacobi s iterative method and the Gauss- Seidel iterative method, and finally gives successive over relaxation iterative method of projection formula and the convergence condition.

在数据库中发现频繁模式和关联规则是数据挖掘领域的最基本、最重要的问题。大多数早期的研究采用了类似Apriori算法的产生候选级并测试迭代的途径代价是昂贵的，尤其是挖掘富模式和长模式时，Jiawei Han提出了一种新颖的数据结构FP_tree,及基于其上的FP_growth算法，主要用于有效的进行长模式与富模式的挖掘.本文在讨论了FP_growth算法的基础上，提出了用Visual C++实现该算法的方法，并编写了算法的程序。-found in the database model and the frequent association rules is the area of data mining the most fundamental and important issues. Most of the early studies used a similar Apriori algorithm for the selection of candidates and test-iterative way was costly, particularly mining the rich patterns and long model, Jiawei Han proposed a novel data structure FP_tree and on the basis of their FP_growth algorithm used effectively the model for long and rich patterns of excavation. This paper discussed the FP_growth algorithm on the basis of the Visual C of the algorithm, and the preparation procedure of the algorithm.