code-and-data

基于divide and conquer策略的Sutherland-Hodgeman多边形裁剪算法的Matlab程序(Divide and conquer strategy based on the Sutherland-Hodgeman polygon clipping algorithm of Matlab procedures)

关于图像超分辨率重建的系统设计关键算法,以光学系统简化模型引入,适合大视角的超分辨率重建(With regard to image super-resolution reconstruction of the system design key algorithms in order to simplify the model for the introduction of optical systems, suitable for large view of the super-resolution reconstruction of)

实际的场景，若电梯的最大载客量m=10，设电梯中已有的 客人服从0-10 之间的均匀分布，且电梯中的任意一人在任意一层下的 概率相同，若你在第三层需要乘电梯到第七层，电梯处在第一层，共 8 层。且在每一层等电梯到达他们的目的楼层的客人服从0-3 的均匀分 布此时我们对电梯的运行加一些限 制，即电梯中若有客人未达目的地，电梯不会改变运行方向，求直到 你到达第七层为止，，电梯需停次数的数学期望，并进行计算机模拟验 证。(The actual scene, if the maximum lift capacity m = 10, the elevator has been designed to obey the guests uniformly distributed between 0-10, and the elevator in any one at any level under the same probability, if you The third layer needs to take the elevator to the seventh floor, the elevator in the first layer, a total of 8 layers. And in each level to reach their goals such as the elevator floor guests subject to the uniform distribution of 0-3 at this time we add some restrictions on the operation of the elevator, the elevator if it has not reached the destination guests, the lift will not change the direction, request until you reach the seventh floor so far, the elevator number of mathematical expectation to be stopped, and the computer simulation.)

关于统计工具箱中的一些基本统计命令的PPT讲义(About Statistics Toolbox statistical commands some of the basic PPT notes)

Z源逆变器最大升压控制仿真模块，实现Z源逆变器的最大升压控制。(MAx boost control)

13 level mli with bridge

Boost学习指南 Boost学习指南 Boost学习指南(Boost study Boost study Boost study)

这个是通过matlab这个软件编写程序可以控制温度！达到了理想的结果！开始的程序是用c写的！但是主要还是后面的matlab程序！(This is a program which are writen by software of matlab and can control temperature,then can reached the ideal result! the procedure at the beginning is written with c!,but mainly is still following matlab procedure!)

说明：  介绍灰色系统的相关知识，有助于提高MATLAB对它的求解(Introduction gray system knowledge, contribute to its solution MATLAB)

compress a picture, using kmeans Clustering