distance

基于matlab/simulink的电流源型SMES仿真(Based on matlab/simulink simulation of current source type SMES)

help me to help another

阵列信号中传播算子DOA估计算法MATLAB程序实现,对研究阵列信号的朋友有帮助! (DOA Estimation)

本程序可以实现具有较好相关性的ZC序列，其时频两域相关性很强(The program can achieve better correlation with the ZC sequence, time and frequency domain strong correlation)

A moving target signal for matlab code

说明：  这是CA码的捕获过程仿真，这能帮助我们更好的理解CA的捕获(This is the CA code capture process simulation, which can help us a better understanding of the capture of the CA)

Matlab多种图像边缘检测方法 1、用Prewitt算子检测图像的边缘 2、用不同σ值的LoG算子检测图像的边缘 3、用Canny算子检测图像的边缘 4、图像的阈值分割 5、用水线阈值法分割图像 6、对矩阵进行四叉树分解 7、将图像分为文字和非文字的两个类别 8、形态学梯度检测二值图像的边缘 9、形态学实例——从PCB图像中删除所有电流线，仅保留芯片对象(Matlab a variety of image edge detection method 1, using Prewitt operator edge detection image 2, with different values of σ LoG operator edge detection image 3, the detection operator Canny edge image 4, image segmentation threshold 5, water line image segmentation threshold 6, on the matrix quadtree decomposition of 7, the image is divided into text and non-text for these two types of 8, detection of morphological gradient of the edge binary image 9, morphological examples- from the PCB images to remove all current lines, retaining only the target chip)

说明：  实验目的 本次实验与书中第二章及3.2节的部分内容有关，包括以下几个部分： （1）开始使用MATLAB （2）显示图像，理解图像的模型 （3）使用图像的不同格式，理解图像压缩的意义 （4）对图像做简单的操作 本次实验需要熟练使用以下几个MATLAB命令： imread, imwrite, imshow,figure (Experimental purposes of this experiment with the book, chapter and part of the contents of 3.2, including the following sections: (1) start using MATLAB (2) show the images, understanding image model (3) the use of images in different formats, understand the significance of image compression (4) on the image to do a simple experiment needs to operate the skilled use of the following MATLAB command: imread, imwrite, imshow, figure)

this is a project about a homework university, enjoy

说明：  matlab编程，实现灰色预测模型,基于当前已有的数据，用来预测未来一段时间内的发展趋势，对于线性发展趋势拟合情况很好，对于非线性预测差一点。(matlab programming, gray prediction model based on the current available data to predict future trends over time, the linear trends fit in good condition, almost nonlinear prediction.)