代码搜索:Fitting

找到约 695 项符合「Fitting」的源代码

代码结果 695
www.eeworm.com/read/386034/8770546

res osr.res

******OPTIMAL SUBSET REGRESSION****** MEANS OF X AND Y 132.35 162.77 116.09 78.7711541.70 61.63 1ORDER REGRESSION SET
www.eeworm.com/read/384416/8871779

res osr.res

******OPTIMAL SUBSET REGRESSION****** MEANS OF X AND Y 132.35 162.77 116.09 78.7711541.70 61.63 1ORDER REGRESSION SET
www.eeworm.com/read/179152/9368158

m exp2_15.m

%curve fitting of sin wave clc clear x=0:0.1:2*pi; %生成样本点x y=sin(x)+0.5*rand(size(x)); %生成样本点y,通过随机矩阵 p=polyfit(x,y,3) %拟合出多项式(3阶) y1=polyval(p,x); %求多项式的值 plot(x,y,'+',x,y1,'-r') %绘制多项式曲线,以验证结
www.eeworm.com/read/177691/9440221

m exp2_15.m

%curve fitting of sin wave clc clear x=0:0.1:2*pi; %生成样本点x y=sin(x)+0.5*rand(size(x)); %生成样本点y,通过随机矩阵 p=polyfit(x,y,3) %拟合出多项式(3阶) y1=polyval(p,x); %求多项式的值 plot(x,y,'+',x,y1,'-r') %绘制多项式曲线,以验证结
www.eeworm.com/read/372266/9514657

m exp2_15.m

%curve fitting of sin wave clc clear x=0:0.1:2*pi; %生成样本点x y=sin(x)+0.5*rand(size(x)); %生成样本点y,通过随机矩阵 p=polyfit(x,y,3) %拟合出多项式(3阶) y1=polyval(p,x); %求多项式的值 plot(x,y,'+',x,y1,'-r') %绘制多项式曲线,以验证结
www.eeworm.com/read/372259/9515110

m exp2_15.m

%curve fitting of sin wave clc clear x=0:0.1:2*pi; %生成样本点x y=sin(x)+0.5*rand(size(x)); %生成样本点y,通过随机矩阵 p=polyfit(x,y,3) %拟合出多项式(3阶) y1=polyval(p,x); %求多项式的值 plot(x,y,'+',x,y1,'-r') %绘制多项式曲线,以验证结
www.eeworm.com/read/371640/9543589

res osr.res

******OPTIMAL SUBSET REGRESSION****** MEANS OF X AND Y 132.35 162.77 116.09 78.7711541.70 61.63 1ORDER REGRESSION SET
www.eeworm.com/read/362596/9989346

m exp2_15.m

%curve fitting of sin wave clc clear x=0:0.1:2*pi; %生成样本点x y=sin(x)+0.5*rand(size(x)); %生成样本点y,通过随机矩阵 p=polyfit(x,y,3) %拟合出多项式(3阶) y1=polyval(p,x); %求多项式的值 plot(x,y,'+',x,y1,'-r') %绘制多项式曲线,以验证结
www.eeworm.com/read/355530/10258991

m exp2_15.m

%curve fitting of sin wave clc clear x=0:0.1:2*pi; %生成样本点x y=sin(x)+0.5*rand(size(x)); %生成样本点y,通过随机矩阵 p=polyfit(x,y,3) %拟合出多项式(3阶) y1=polyval(p,x); %求多项式的值 plot(x,y,'+',x,y1,'-r') %绘制多项式曲线,以验证结
www.eeworm.com/read/355063/10298060

res osr.res

******OPTIMAL SUBSET REGRESSION****** MEANS OF X AND Y 132.35 162.77 116.09 78.7711541.70 61.63 1ORDER REGRESSION SET