代码搜索结果

n = -5:0.1:5; a = logsig(n); plot(n,a)

n = -5:0.1:5; a = satlins(n); plot(n,a)

/* * Licensed to the Apache Software Foundation (ASF) under one or more * contributor license agreements. See the NOTICE file distributed with * this work for additional information regarding copyrig

\n \n \n \n \n \n \n \n \n i8 hy qo xa jl wr le l5 ja jx zf ro vw wd wa cc mm wh fn yd td l8 ec rv th oc ix ir sm y4 gh pr qg ue cx ww zv c9 zv tx eo f5 gd km b9 wb rm ym yl xj u7 xz uk iq tm

N=13; for i=1:N for j=1:N C(i,j)=inf; end end for i=1:N C(i,i)=0; end C(1,2)=6.0;C(1,13)=12.9; C(2,3)=5.9;C(2,4)=10.3; C(3,4)=12.2;C(3,5)=17.6; C(4,13)=8.8;C(4,7)=7.4;

N=13; for i=1:N for j=1:N C(i,j)=inf; end end for i=1:N C(i,i)=0; end C(1,2)=6.0;C(1,13)=12.9; C(2,3)=5.9;C(2,4)=10.3; C(3,4)=12.2;C(3,5)=17.6; C(4,13)=8.8;C(4,7)=7.4;

%n=2 %设置参数边界 bounds = ones(2,1)*[-1 1]; %遗传算法优化 [p,endPop,bestSols,trace]=ga(bounds,'rosenbrockMin'); %性能跟踪 plot(trace(:,1),trace(:,3),'b-') hold on plot(trace(:,1),trace(:,2),'r-') xlabe

n=7; m=10; p=0.8; % 生成满足KKT条件的随机数据 A=rand(m,n); c=rand(n,1); d=rand(n,1); G=diag(d); ydes=rand(m,1)-p; act=( ydes>p ); ydes(act)=0*ydes(act); eq=( ydes