Main_ComplexAutoCorrelation.m

description sur la QAM sur simulink

非线性动力学求解轴承约束边界稳定性问题，理论分析(Solve problems of bearing stability constraint boundary nonlinear dynamics, theoretical analysis)

美国UDDS工况matlab模型，用于模拟UDDS工况，对自己设计的模型进行分析(UDDS model of the United States MATLAB, used to simulate the UDDS conditions, the design of their own model analysis)

这个是对PL-logdist和PL-lognormal的一个仿真。程序简单易懂，但是意义不小。有专门的画图子程序。(This is a PL-logdist and PL-lognormal a simulation. Procedures are simple, but the meaning is not small. Have a special drawing routines.)

target image program in zip file

最优化计算方法中 有关于拟牛顿法的一段小代码 可以看看(Optimization method in the Quasi-Newton method on a small section of code that can look at)

基于灰度的归一化匹配算法：将原图以及匹配图灰度化，算出相关系数后得到匹配区域。(Based on Gray' s normalized matching algorithms: the original image and the gray level of matching graph, calculate the correlation coefficient obtained after the matching area.)

ABS是关于汽车防抱死制动系统的simulink，程序截图(ABS is simulink automotive anti-lock braking system on the program screenshot)

说明：  Market Newman写的复杂网络的加权GN算法 算法用Python写的 其基本思想是不断的删除网络中具有相对于所有源节点的最大的边介数(ege betweenness)的边，然后，再重新计算网络中剩余的边的相对于所有源节点的边介数(The basic idea is to delete the network with respect to all of the source nodes of the largest betweenness (EGE betweenness) edges, then re computing network the remaining edge relative to the boundary of the source node number of all)

matlab开发环境，．编程实现二维DFT的变换，并与标准函数结果fft2进行比较，基本傅里叶、离散余弦变换，空域（完成两个程序） 增强噪声后再进行处理，利用标准函数，求图像阈值分割、边缘检测的基本使用（lena256.bmp，方法：graythresh、edge），求分水岭，利用标准函数dwt2、idwt2分解图像man_pic.jpg，基本 BP-BPbase1 (matlab development environment. Programming dimensional DFT transform, and with the standard functions compare results fft2 basic Fourier, discrete cosine transform, airspace (to complete the two programs) to enhance the noise and then processed using standard functions for image thresholding, edge Detection of basic use (lena256.bmp, method: graythresh, edge), seeking watershed, using a standard function dwt2, idwt2 decomposed image man_pic.jpg, basic BP-BPbase1)