Sheath_oneIon1D

Matlab小问题 问: Matlab仿真中怎样编辑Scope中的图象??? 答: 实现的方法有以下的几种: 1）PrintScreen，然后粘贴到Windows位图编辑器，选择图像点击右键，选择“反色”即可； 2）在Scope中，它的参数设置的第二页，有一个Save Data to Workplace，将它选中，然后在下面的方框 中指定变量名，然后用plot命令画出； 3）直接在模型上再加一个，to Workplace模块，也用plot画出； 4) 等scope显示出来图像以后，在matlab上运行 set(0, ShowHiddenHandles , On ) set(gcf, menubar , figure ) 这时候你会发现scope的工具栏的上面多了一行，点击insert-axes，鼠标会变成十字形状，然后再图像的任意一处双击左键出现一个对话框PropertyEditor，选中style在窗口的右便会出现color，这时你就可以任意修改背景颜色了。 问: 怎样进行S-function的编程和使用??? 答: S-function也就是System-function的缩写。说得简单，S-function就是用MATLAB所提供的模型不能完全满足用户，而提供给用户自己编写程序来满足自己要求模型的接口。要了(err)

用于图像处理等等，在MATLAB中实现移动目标的检测与辨识。(Used in image processing and so on, is realized in MATLAB moving target detection and recognition.)

this is a Demand response programing. Offer cost minimization with Emergency demand response programming. OCM+EDRP

利用PWM脉宽控制的半桥电路实现的DCDC变换器(The converter that use the PWM to control the voltage of the output。 )

说明：  MATLAB常用命令大全，涵盖常用命令，很有实用价值。(MATLAB commonly used commands Guinness, cover the commonly used commands, very practical.)

说明：  利用Matlab软件平台对JTC进行了图像识别仿真实验，得到了二维及三维相关输出图像，显示出尖锐的相关峰。仿真实验表明：联合变换进行图像识别中存在强烈的零级干扰，干扰信号是有用信号的7.14倍，输出结果不理想；采用功率谱相减法可以消除零级强干扰，进而提高了图像的识别能力。(Simulations of joint transform correlator (JTC) using Matlab is implemented, and the 2-D and 3-D drawings of the correlation image are obtained. In the simulation experiments, the sharper correlation peaks are showed. The result shows that strong disturbance of zero rank exists in the simulation of JTC, and it is 7.14 times stronger than the useful signal thus, the power spectrum subtraction is used to eliminate the strong disturbance, and the capacity of image recognition is improved.)

说明：  基于运动模糊图像产生的原因，自编一个生产运动模糊图像的matlab程序，程序 需要输入模糊长度，默认模糊角度为0，包含一张图片(Based on the causes of motion blurred image, self production of motion blurred images of a matlab program, the program requires input fuzzy length, the default fuzzy angle 0)

对于粒子群算法和MATLAB学习者有很大帮助，非常好用的。(PSO algorithm and MATLAB for learners of great help, very useful.)

基于类覆盖算法和粒子群优化的神经网络解决模式分类问题(algorithm based on the type coverage and PSO the neural network model to solve classification problems)

此文档包含支持向量机程序和核函数的编写程序(This document contains the program of support vector machine and kernel programming)