transfer

Borland C++Builder与MATLAB混合编程之COM实现方法(Borland C Builder and MATLAB's programming mixed COM method)

说明：  电力系统潮流上机程序，已知线路结构，pq节点，pv节点和平衡节点，求各点的未知量。(Power System Power program, known line structure, pq node, pv nodes and balancing node, find the unknown amount of points.)

WRK实验所需要软件的参考说明（Windbg）(inactivated laboratory reference to the need for software (Windbg))

多径信道仿真程序的一部分，不全，抱歉了，希望有用(duojingxindao bianmachengxu)

Serial port communication for kwp 2000 fast initialization. this code is not complete. I am trying to develop it

matlab与vc联合编程 实现图形的动态显示(matlab and graphics vc joint programming to achieve the dynamic display)

这个小软件可以做到软件内的网页跟随软件变大变小(新手)(In software s homepage followed software fill-out changes small (novice) )

说明：  在过去的几年中, 背包问题吸引了众多理论研究人员和应用工作者的注意力, 因而得到了广泛而深入的研究。理论方面, 研究兴趣主要来自于该问题简单的结构, 而这种特点既可以深入探索许多组合特性, 又可以通过解决一系列背包子问题来最终求解更为复杂的优化问题。实践方面, 这些问题可以表述许多工业场合的应用, 最典型的应用包括货 物装载、存储分配和资本预算等等。在寻找背包问题可行解的过程中, 出现了众多的算法, 本文是利用MATLAB 程序求背包问题可行解的一种算法。(In the past few years, knapsack problem has attracted many researchers and application of theoretical attention of workers, which has been extensive and in-depth study. Theory, research interest mainly from the simple structure of the problem, and this characteristic combination of both in-depth exploration of many features, but also can solve a series of knapsack sub-problems to solve more complex final optimization problem. Practice, these problems can be expressed in many industrial applications where the most typical applications include cargo loading, storage, distribution and capital budgets, and so on. Knapsack problem in finding feasible solutions in the process, there have been many algorithms, this is the knapsack problem using MATLAB program seeking a feasible solution algorithm.)

采用c++调用matlab写的一个sift算法，其中调用matlab只是使用其中几个函数。可以很准确的检测出sift特征点。(Using c++ to call a matlab write sift algorithm, which used to call only a few matlab function. Can accurately detect the feature points sift.)

在MATLAB实现的用C实现的KNN算法，输入训练数据文件，和test文件，进行预测分类，并且可以与真实情况比较测试预测正确百分比(Implemented in MATLAB KNN algorithm implemented in C, the input training data file, and test files, to predict the classification and testing with the real situation is more correct percentage of predicted)