代码搜索:M

找到约 10,000 项符合「M」的源代码

代码结果 10,000
www.eeworm.com/read/166174/10030830

m 提取.m

clear; load key X=double(imread('lenaattack2.jpg')); [XCsource,XSsource]=wavedec2(X,3,'db1'); low=XCsource(1:4096); lowarray=reshape(XCsource(1:4096),64,64); std=result; for i = 1:64
www.eeworm.com/read/166173/10030835

m 嵌入.m

clear; X=double(imread('lena.bmp')); [XCsource,XSsource]=wavedec2(X,3,'db1'); W=double(imread('UESTC.bmp')); %'double'将矩阵的元素变成双精度元素 lowarray=reshape(XCsource(1:4096),64,64); %convert matrix XCso
www.eeworm.com/read/360358/10100798

m 曲线.m

t=0:0.01:10; g=exp(-0.7*t).*cos(5*t); f=1./(1+t.^2); plot(t,f,'r'); hold on; plot(t,g,'b'); grid on; xlabel('时间','FontSize',24); ylabel('幅度','FontSize',24); title('Matlab入门/陈什江,9月18日','FontSi
www.eeworm.com/read/355580/10255858

m a.m

clear;clc; lb=zeros(3,4); ub=inf*ones(3,4); ub(1,2)=2; ub(2,3)=1.5; ub(3,4)=1; x0=lb; [x,f]=fmincon(@afun,x0,[],[],[],[],lb,ub,@acon)
www.eeworm.com/read/355433/10266244

m 遍历.m

for m=1:5 %因为从图形可看出5年后,药性减弱,不会是我们的优化结果 [t,x]=ode45('shu4',[0,m],[7,1.7,0.001]); %加药 laoshu1(m)=x(length(t),2); %m年后老鼠量 cao1(m)=x(length(t),1); %m年后草的量 cz
www.eeworm.com/read/161420/10414860

m 临时.m

LP.lr=0.1; %学习速率 net.trainParam.show=20; for i=1:k p_1(i,:)=(p_1(i,:)-min(p_1(i,:)))/(max(p_1(i,:))-min(p_1(i,:))); end for i=1:k t_1(i,:)=(t_1(i,:)-min(t_1(i,:)))/(
www.eeworm.com/read/161420/10414875

m 测试.m

%%%%%%%%%%%%%%%%从EXCEL载入初始数据%%%%%%%%%%%%%%%% a=[data]; %%%%%%%%%%%%%%%%变量定义%%%%%%%%%%%%%%%% L=240 ; %%%%%股价历史数据总数%%%%% n=3 ; %%%%%神经网络输入数据数量%%%%% m=1 ; %%%%%神经网络输出数据数量%%%%% k=L-(
www.eeworm.com/read/424063/10500037

m are.m

function X = are(A,B,C) %ARE Algebraic Riccati Equation solution. % X = ARE(A, B, C) returns the stablizing solution (if it % exists) to the continuous-time Riccati equation: % % A'
www.eeworm.com/read/424027/10505999

m 量化.m

function Q_IMG = quantization(IMG); %对IMG进行8*8 JPEG量化,结果存于Q_IMG %% 8*8 JPEG量化矩阵 JPEG_data = [16 11 10 16 24 40 51 61 12 12 14 19 26 58 60 55 14 13 16 24 40 57 69 56 14 17 22 29 51 87 80 62 1
www.eeworm.com/read/160516/10522934

m or.m

%OR Dataset overload