可以用二分法来解非线性方程解方程，简单的程序代码，虽简单，但很实用...

查阅了一下资料，编写的二维大津法算法实现，描述了二维ostu 算法的实现，在vc++上实现，里面有具体的注释。

windows小帮手,vc6.0开发的,有点小问题-windows Assistant, vc6.0 developed a bit small problem

矩阵类，可实现矩阵的各种运算，包括加减乘除、求逆等。-Matrices can realize a variety of matrix operations, including multiplication and division addition and subtraction, inversion and so on.

用于求解环境污染物在地下水中迁移规律的解析解-for solving environmental pollutants in the groundwater migration laws of the analytic solution

这个函数ObjectDetection Viola-Jones中检测的实现框架。在这个框架Haar-like特性用于快速目标检测。它支持训练分类器OpenCV的XML文件,可以在opencv.willowgarage.com上下载作为OpenCV的一部分软件

利用C++完成计算方法的分段线性，二次插值和全区间拉格朗日插值的计算！-C completed the calculation method piecewise linear, quadratic interpolation, and the region between the Lagrange interpolation calculation!

poj 2408 解题代码，北大acm在线可以测试。-problem-solving poj 2408 code, North acm test online.

资源描述CS7495 Final Project  Sooraj Bhat Object Removal by Exemplar-based Inpainting USING THE CODE Everything was done in Matlab and MEX (i.e. a C function callable from Matlab).  First, the C code needs to be compiled.  At the Matlab prompt, type:    mex bestexemplarhelper.c You should then be able to run the following (which takes ~2mins on my 2GHz Pentium 4 laptop with 256MB of RAM):    [i1,i2,i3,c,d,mov] = inpaint("bungee0.png","bungee1.png",[0 255 0]); A smaller run (~25 seconds) would be:    [i1,i2,i3,c,d,mov] = inpaint("bw0.png","bw2.png",[0 255 0]); To visualize:    plotall;    close; movie(mov); SAMPLE IMAGES & RESULTS *0.png      The original images ("bw" and "bungee") *{1,2}.png    The different fill region masks. *P2.png     &nbs

C++链表操作，从创建一个链表到对链表的增删改查，适合初学算法的朋友学习参考，转自别处，对其进行了一些修改。

TSPTM是一种用于经济模型估算和模拟的完整语言。它是一个用于经济估算的世界标准。虽然TSP主要由经济学家开发并发展,但它的设计并没仅把它限制在经济领域。任何由相同变量的重复观测得到的数据,都可用TSP分析-TSPTM is an economic model for estimation and simulation of a complete language. It is an estimate for the world economy standards. Although the TSP mainly by the development economists and development, but its design does not limit it to only in the economic field. Any repeat of the same variables observed in the data analysis are available TSP