PhD_tool

itti 1988的实验 ，显著性检测，很好的学习资料(itti 1988 experiment, a significant detection, good learning materials)

This folder contains Matlab functions for the Enhanced Interval Approach (EIA) in: Simon Coupland, J. M. Mendel and Dongrui Wu, “Enhanced Interval Approach for Encoding Words into Interval Type-2 Fuzzy Sets and Convergence of the Word FOUs,” IEEE World Congress on Computational Intelligence, Barcelona, Spain, July 2010. All following functions were tested in Matlab 7.4.0 (R2007a) under Windows 7: centroidIT2: Compute the centroid of an IT2 FS. EKM: Implement the Enhanced KM algorithms. IA: Implement the Interval Approach for word encoding. mainJPL: Illustrate IA and EIA using the JPL dataset. mainWeb: Illustrate IA and EIA using the Web dataset. mg: Compute the membership grades of a vector of numbers on a T1 FS. plotFigures: Plot Figs. 3.18, 3.19 and 3.20 in the book. plotIT2: Plot an IT2 FS. Last modified by Dongrui Wu (dongruiw@usc.edu), May 2, 2010.

此段程序可以将seg2数据转换为TSPwin处理的数据。(This section of the program can be converted into data TSPwin seg2 data processing.)

matlab在通信系统仿真第二版 第五章例题代码(matlab second edition of the communication system simulation code example Chapter)

二维FDTD的MATLAB的源程序，以直径为6cm的金属圆柱为例。(Two-dimensional FDTD the MATLAB source to a diameter of 6cm metal cylinder as an example.)

mfile for matlab program

说明：  我编写的基于颜色分量的汽车牌照定位识别。主要有以下几步：1 基于颜色分量的灰度值识别出车牌（基于蓝色车牌）2 从蓝色区域中识别白色的号码(prepared by the color components based on the vehicle license location identification. The following are the main steps : a component based on the color of gray values identification plates (based on blue plates) 2 from the blue and white identification numbers)

说明：  是自己论文中编写的无线传感器网络中簇间路由分层次通讯方法的matlab仿真代码，可以直接出生存期图。很多论文都用这个思想。(Matlab simulation, an improved version of the leach agreement between the clusters, the passing of a hierarchical routing protocol to send a message, many papers use this thought, just write and run directly displayed a life cycle)

基于matlab的典型IEEE 9节点系统潮流计算(matlab, ieee 9, load flow)

假设已经获得不同目标类型的一组特征值，这是可以通过模糊聚类获取哥哥目标类型在特征空间商的聚类中心，当测量到某个目标的特征值，可以通过计算目标特征为止与各个聚类中心之间的距离来判定目标的类型。(matlab fcm)