代码搜索：差分走线
找到约 8,331 项符合「差分走线」的源代码
代码结果 8,331
www.eeworm.com/read/129636/14234911
m exm040522_1.m
F=[1,2,3;4,5,6;7,8,9]
Dx=diff(F) %相邻行差分
Dx_2=diff(F,1,2) %相邻列差分。第三输入宗量2表示“列”差分。
[FX,FY]=gradient(F) %数据点步长默认为1
[FX_2,FY_2]=gradient(F,0.5) %数据点步长为0.5
www.eeworm.com/read/212376/15157221
m exm040522_1.m
F=[1,2,3;4,5,6;7,8,9]
Dx=diff(F) %相邻行差分
Dx_2=diff(F,1,2) %相邻列差分。第三输入宗量2表示“列”差分。
[FX,FY]=gradient(F) %数据点步长默认为1
[FX_2,FY_2]=gradient(F,0.5) %数据点步长为0.5
www.eeworm.com/read/268719/11124590
cpp newton.cpp
float f(float x[],float y[],int s,int t)//牛顿插值法，用以返回差商
{
if(t==s+1)
return (y[t]-y[s])/(x[t]-x[s]);
else
return (f(x,y,s+1,t)-f(x,y,s,t-1))/(x[t]-x[s]);
}
www.eeworm.com/read/200131/15440155
m exm040522_1.m
F=[1,2,3;4,5,6;7,8,9]
Dx=diff(F) %相邻行差分
Dx_2=diff(F,1,2) %相邻列差分。第三输入宗量2表示“列”差分。
[FX,FY]=gradient(F) %数据点步长默认为1
[FX_2,FY_2]=gradient(F,0.5) %数据点步长为0.5
www.eeworm.com/read/286478/8763088
m matlab的差分算法实现.m
function dedemov(action);
% DE function minimization demonstration.
% dedemov is called with no parameters.
%
% Differential Evolution for MATLAB
% Copyright (C) 1996 R. Storn
% International Co
www.eeworm.com/read/361544/10047207
kdh 差分进化算法及其应用.kdh
www.eeworm.com/read/467915/6996928
vbw 水准网平差12.2.vbw
Form1 = 0, -24, 893, 623, , 95, 48, 598, 503, C
form2 = 154, 203, 757, 634, C, 26, 68, 624, 569, C
www.eeworm.com/read/467915/6996960
vbp 水准网平差12.2.vbp
Type=Exe
Form=水准网平差.frm
Reference=*\G{00020430-0000-0000-C000-000000000046}#2.0#0#C:\WINDOWS\system32\stdole2.tlb#OLE Automation
Form=水准网2.frm
Object={F9043C88-F6F2-101A-A3C9-08002B2F49FB}#1.2#0;
www.eeworm.com/read/447935/7543814
vbp 平面控制网间接平差.vbp
Type=Exe
Form=平面控制网间接平差.frm
Reference=*\G{00020430-0000-0000-C000-000000000046}#2.0#0#C:\WINDOWS\system32\stdole2.tlb#OLE Automation
Object={F9043C88-F6F2-101A-A3C9-08002B2F49FB}#1.2#0; COMDLG32.OC
www.eeworm.com/read/447935/7543818
vbw 平面控制网间接平差.vbw
frmMain = 44, 58, 944, 565, , 22, 29, 811, 655, C
mdlAdjust = 154, 203, 1054, 709,