matlab

说明：  图像分割是一种重要的和关键的图像分析技术，其目的是把图像分成各具特性的区域并提取出感兴趣的部分，图像分割的结果是图像特征提取和识别等图像理解的基础。对它的研究一直是图像技术研究中的热点和焦点，提出了数以千计的不同算法，虽然这些算法大都在不同程度上取得了一定的成功，但是图像分割问题还远远没有解决，这方面的研究仍然面临很多挑战。(Image segmentation is an important and critical image analysis, the purpose is to image into regions with different characteristics and extract the interesting part, the result of image segmentation is the image feature extraction and recognition based on image understanding. Study it has been a hot spot imaging technology research and focus, made thousands of different algorithms, although most of these methods to varying degrees, achieved some success, but the image segmentation problem is far from resolved, it of research still faces many challenges.)

《提问的智慧》，作为一个程序员，你曾经遇到过在论坛上发帖无人问津，看看提问的智慧把(" Question the wisdom" as a programmer, you have encountered no one is interested to post in the forum to see the wisdom of the questions)

matlab code for cryptography

optimal assignment algorithm

svm优化算法，利用改进的随机森林对SVM参数进行优化，提高运算精度和速度。(SVM optimization algorithm, the parameters of SVM are optimized by using random forest improvement, improve the calculation precision and speed.)

基于支路电流的辐射型配电网潮流程序，实现配电网的优化潮流(Based on branch currents of the radiant power flow program, the optimization of distribution networ)

k-means 算法接受输入量 k ；然后将n个数据对象划分为 k个聚类以便使得所获得的聚类满足：同一聚类中的对象相似度较高；而不同聚类中的对象相似度较小。聚类相似度是利用各聚类中对象的均值所获得一个“中心对象”（引力中心）来进行计算的。(k-means algorithm accepts input k then n data objects into k clusters in order to make clustering satisfy obtained: the objects in the same cluster high similarity different clustering object similarity small. Cluster similarity is the use of the mean of each cluster of objects that get a " central object" (center of gravity) to perform the calculation.)

MATLAB语音信号分析与合成（第二版）宋知用_例程(MATLAB Speech Signal Analysis and Composition (Second Edition) Song Zhiyu Routine)

基于传递函数模型的PID控制matlab代码(PID control based on the transfer function model matlab code)

matlab与modelsim的联调教程，pdf格式的(matlab FBI and the modelsim tutorial, pdf format)