edge_detect

卡尔曼滤波程序，C++/C,matlab.(Kalman filtering procedures, C++/C, matlab.)

matlab源程序 很有用的 你们可以试用一下(matlab source code useful you can try)

说明：  分支定界法（branch and bound）是一种求解整数规划问题的最常用算法。这种方法不但可以求解纯整数规划，还可以求解混合整数规划问题。分支定界法是一种搜索与迭代的方法，选择不同的分支变量和子问题进行分支。 对于两个变量的整数规划问题，使用网格的方法有时更为简单。 [1] 通常，把全部可行解空间反复地分割为越来越小的子集，称为分支；并且对每个子集内的解集计算一个目标下界（对于最小值问题），这称为定界。在每次分枝后，凡是界限超出已知可行解集目标值的那些子集不再进一步分枝，这样，许多子集可不予考虑，这称剪枝。这就是分枝定界法的主要思路。(Branch and bound method is one of the most commonly used algorithms to solve integer programming problems. This method can solve not only pure integer programming but also mixed integer programming. Branch and bound algorithm is a method of search and iteration, which selects branches with different branch variables and sub problems. For integer programming problems with two variables, the grid method is sometimes simpler[ 1] Generally, all feasible solution spaces are divided into smaller and smaller subsets repeatedly, which is called bifurcation; And a lower bound of the objective (for the minimum value problem) is calculated for the solution set in each subset, which is called the bound. After each branch, those subsets whose bounds exceed the objective value of the known feasible solution set will not be further branched, so many subsets can not be considered, which is called pruning. This is the main idea of branch and bound method.)

detecting the Edge from an image with the filter

经过自己长时间的学习，编写了可实现机器人PID控制的matlab仿真程序。(Through their long learning, written a robot PID control matlab simulation program.)

αβγ滤波器，αβ滤波器，卡尔曼滤波器仿真实例。(Simulation examples of alpha beta gamma filter, alpha beta filter and Kalman filter.)

DRNN神经网络自学习PID解藕控制，与PID相比具有抗干扰能力强特点(DRNN self-learning neural network PID control solution lotus, compared with PID characteristics of anti-interference ability)

Sample program to study Location Determination Techniques using OTDOA

基于MATLAB环境下偏微分方程组的求解对应的代码 简单明了 便于初学者学习使用(Based on the MATLAB environment to solve partial differential equations corresponding code is simple for beginners to learn to use)

Leaf disease detection