是学语言的课程设计,好象是查找或是迷宫

普里姆构造最小生成树算法 图或网的邻接矩阵表示及其上基本算法的实现-prim minimum spanning tree algorithm tectonic map of the network or matrix and adjacency on the realization of basic algorithm

用vb编写遗传算法，实际应用部分（如适应度函数需要自己编写，程序中已注明），此为转载代码-Vb prepared using genetic algorithm, the practical application of some (such as the fitness function needs its own written procedures have been specified), this is reproduced in the code

匈牙利算法,利用C实现.可以用,我试过,转自别出.-Hungarian algorithm, using C realize. Can be used, I tried, carried out another.

可以把二进制数据（比如您从ASP的Request.BinaryRead方法得到的数据）转换为字符串。-Can be binary data (such as your method from the ASP

* 用改进的欧拉方法求解初值问题，其中一阶微分方程未y =f(x,y) * 初始条件为x=x[0]时,y＝y[0]. * 输入: f--函数f(x,y)的指针 * x--自变量离散值数组(其中x[0]为初始条件) * y--对应于自变量离散值的函数值数组(其中y[0]为初始条件) * h--计算步长 * n--步数 * 输出: x为说求解的自变量离散值数组 * y为所求解对应于自变量离散值的函数值数组 -* Improved Euler method to solve initial value problems, not an order differential equation y = f (x, y)* initial conditions for x = x [0], y = y [0].* Input : f-- function f (x, y)* x pointer-- from the array variable discrete values (x [0] for the initial conditions)* y-- corresponding to the variable discrete value of the function of the array (y [0] for the initial conditions)* h-- calculated step* n-- steps* output : Solving for x that the variable array* discrete values by solving y variables corresponding to the value of the discrete function arrays

清华大学DSK5416实验指导书，含有ccs指导，参考实验，较具参考价值-Tsinghua University DSK5416 experimental guide book, containing ccs guide, reference experiment, the reference value

通过一句 的问答方式，详细讲解了LINUX的一些操作。-through one ask after one ask ,insight the operation of linux system.

Note:通过模拟量输入口LINE_IN输入电压值，以8K的采样率经A/D //转换后送给IOB口控制LED点亮,同时可以根据LED的点亮来了解转换 //的数据-Note : Analog inputs LINE_IN input voltage value to 8K by the sampling rate A/D// conversion gave Privalov population control LED lights, LED can be lit to understand the conversion// data

stv0299资料，pdf文档，dvb-s解调芯片-stv0299 information, pdf documents, dvb-s demodulator chip

主要关于web使用挖掘的介绍，非常不错的文章。-mainly on the use of web mining, a very good article.