FFT-and-MATLAB

这是一个非常好的关于OFDM的英文文章，它是国外的博士论文，对于想了解整个OFDM的朋友来说，可以了解到许多中文文章所没有的知识。(This is a very good article in English on OFDM, which is the doctoral thesis abroad, who want to understand the overall OFDM' s friends, you can understand that many Chinese do not have knowledge of the article.)

基于文化算法的粒子群优化算法能记忆遍历过的最优值(Culture-based particle swarm optimization algorithm to traverse through the optimal value of the memory)

直方图相关内容，有兴趣的人可以看一下，用matlab编写的m文件(Histogram content, those who are interested can look at using matlab m file)

matlab power quality

利用文本读取方法，从一个很长的数据文本中截取所要处理的数据段。(The text read by means of data from a long interception of text data segment to be processed.)

双目资料，很好的学习资料，帮助很大，谢谢大家(Binocular information, good learning materials, helpful, thank you)

程序代码说明 P0401：用Prewitt算子检测图像的边缘 P0402：用不同σ值的LoG算子检测图像的边缘 P0403：用Canny算子检测图像的边缘 P0404：图像的阈值分割 P0405：用水线阈值法分割图像 P0406：对矩阵进行四叉树分解 P0407：将图像分为文字和非文字的两个类别 P0408：形态学梯度检测二值图像的边缘 P0409：形态学实例——从PCB图像中删除所有电流线，仅保留芯片对象 ( Procedure code explanation P0401: Examines the picture with the Prewitt operator the edge P0402: Examines the picture with the different sigma value LoG operator the edge P0403: Examines the picture with the Canny operator the edge P0404: Picture threshold value division P0405: Divides the picture with the water line threshold value law P0406: Carries on to the matrix four forks the tree decomposition P0407: Divides into the writing and the non- writing two categories the picture P0408: The morphology gradient examines two values pictures the edge P0409: The morphology example 鈻♀枴deletes all electricity streamline from the PCB picture, only retains the chip object )

这是关于UKF（无味卡尔曼滤波算法）算法的matlab程序(This is on the UKF algorithm matlab program)

乘子法也是最优化中经常使用的一种传统数学优化方法，对于学习最优化的同学很有用处。(Multiplier Method is the most conventional mathematical optimization methods often used in optimization, optimization for the students to learn useful.)

SVDD的工具箱，可以很好的处理一类分类问题，详见Support Vector Data Description一文(SVDD tools，can be used to process one class classification problem,for more details ,we refer to "Support Vector Data Description")