P0207

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.)

This toolbox was designed as a teaching aid, which matlab is particularly good for since source code is relatively legible and simple to modify. However, it is still reasonably fast if used with the supplied optimiser. However, if you really want to speed things up you should consider compiling the matrix composition routine for H into a mex function. Then again if you really want to speed things up you probably shouldn t be using matlab anyway... Get hold of a dedicated C program once you understand the algorithm.

粒子群做非线性模型的参数估计，已检测很好用(nonlinear parameter estimation)

对二分类数据集分类，计算准确率并画出分界面(Classification of the two data sets classification, calculation accuracy and to draw the interface )

仿照正态分布normpdf，写的一个柯西分布概率密度函数(Cauchy P.D.F)

文章Clustering by fast search and find of density peaks里的聚类算法代码(clustering algorithm matlab code in paper:Clustering by fast search and find of density peaks)

Window网络与通信 书的配套源码(Window networking and communications supporting the FO)

Frequency Domain Method to calculate the Difference of Arrival of Sound.

基于马尔科夫随机场的过绿色模拟退火的分割方法程序，包含如何建立马尔科夫随机场。(Markov random field segmentation method for green program based on simulated annealing, including how to build the Markov random field.)

实现加权最小二乘拟合，经典的系统辨识方法，很管用(Achieve a weighted least-squares fitting, classical system identification methods, it is useful)