Matlab 和Smulink 制冷空调仿真资料集（资料+代码+案例）

【实例简介】

差分演化算法的matlab程序: function DE(Gm,F0)%差分进化算法程序基本程序%F是变异率   F0=0.6 Gm=1000; %最大迭代次数Np=100; %种群规模CR=0.9;  %杂交参数G=1;%初始化代数D=0;%所求问题的维数eps=1e-9;%精度ge=zeros(1,Np);%各代的最优值bestx=zeros(Np,D);%各代的最优解%产生初始种群%xmin=-10;xmax=100;%带负数的下界xmin=-5.12;xmax=5.12;%-----函数值计算-----------function result=DEMB(XX);     sol=XX;     result=0;for i=1:D    result=result sol(i)^2;    %y=sum(XX.^2-10.*cos(2.*pi.*XX) 10);endend%---------------------------X0=(xmax-xmin)*rand(Np,D) xmin;X=X0;%%%%%%%%%%变异操作X1new=zeros(Np,D);%初始化X1_new=zeros(Np,D);%初始化X1=zeros(Np,D);%初始化value=zeros(1,Np);while Gxmin)&(bonCR %利用二项分布来交叉            X1_new(i,:)=X(i,:);        else            X1_new(i,:)=X1new(i,:);        end    end %%%%%%%%%%%%%%%竞争操作    for i=1:Np     if DEMB(X1_new(i,:))

直驱风机发电机（PMSG_windfarm_MMC_VF_1214.slx）

【实例简介】

不同阵列天线进行方向图的绘制

阵列信号处理中的传播算子DOA估计算法MATLAB程序

论文《As-Projective-As-Possible Image Stitching with Moving DLT》中的拼接算法，对于视差图像拼接具有一定的鲁棒性，但是对特征点数量及其分布均匀性有较高的要求。 The success of commercial image stitching tools often leads to the impression that image stitching is a “solved problem”.The reality, however, is that many tools give unconvincing results when the input photos violate fairly restrictive imaging assumptions;the main two being that the photos correspond to views that differ purely by rotation, or that the imaged scene is effectively planar.Such assumptions underpin the usage of 2D projective transforms or homographies to align photos. In the hands of the casual user,such conditions are often violated, yielding misalignment artifacts or “ghosting” in the results. Accordingly, many existing imagestitching tools depend critically on post-processing routines to conceal ghosting. In this paper, we propose a novel estimationtechnique called Moving Direct Linear Transformation (Moving DLT) that is able to tweak or fine-tune the projective warp toaccommodate the deviations of the input data from the idealized conditions. This produces as-projective-as-possible image alignmentthat significantly reduces ghosting without compromising the geometric realism of perspective image stitching. Our technique thuslessens the dependency on potentially expensive postprocessing algorithms. In addition, we describe how multipleas-projective-as-possible warps can be simultaneously refined via bundle adjustment to accurately align multiple images for largepanorama creation.

相控阵天线方向图的不同画法3(Beam_F2.m)

实现一个针对《数字信号处理》课程的仿真系统，通过该系统可以演示或验证课程所学的内容。要求程序具有界面，并能实现以下功能：       1）能产生或得到各种数字信号（sin、方波、三角波、语音、噪声及其叠加），叠加噪声信号的噪声强度需要从键盘或鼠标输入，并显示时域波形；       2）具有DFT、DCT、DWT和Hilbert变换功能，并显示变换域波形；       3）具有根据需求设计低通、高通和带通滤波器的功能；       4）分别对产生的数字信号和读入的语音信号，显示时域和频域波形，在信号上叠加噪声（信噪比分别为20dB、10dB和5dB），显示时域和变换域波形，通过滤波器对其降噪，得到输出信号的频域特性和时间序列。

【实例简介】现代谱估计  该程序比较了各种谱估计方法的利弊