Matlab Lsqucurvefit 函数 “Function value and YDATA sizes are not equal”clear all;clc;x=[35000 45000 55000];y=[0.5646 0.7374 0.8743];f=@(c,x)(c(2)*x.^c(3)*sin(pi/2*c(3))/(c(1)+c(2)*x.^c(3)*cos(pi/2*c(3))));c0=[10000 10 0.01];[c,resnorm]=lsqcurve
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![Matlab Lsqucurvefit 函数 “Function value and YDATA sizes are not equal”clear all;clc;x=[35000 45000 55000];y=[0.5646 0.7374 0.8743];f=@(c,x)(c(2)*x.^c(3)*sin(pi/2*c(3))/(c(1)+c(2)*x.^c(3)*cos(pi/2*c(3))));c0=[10000 10 0.01];[c,resnorm]=lsqcurve](/uploads/image/z/14054833-1-3.jpg?t=Matlab+Lsqucurvefit+%E5%87%BD%E6%95%B0+%E2%80%9CFunction+value+and+YDATA+sizes+are+not+equal%E2%80%9Dclear+all%3Bclc%3Bx%3D%5B35000+45000+55000%5D%3By%3D%5B0.5646+0.7374+0.8743%5D%3Bf%3D%40%28c%2Cx%29%28c%282%29%2Ax.%5Ec%283%29%2Asin%28pi%2F2%2Ac%283%29%29%2F%28c%281%29%2Bc%282%29%2Ax.%5Ec%283%29%2Acos%28pi%2F2%2Ac%283%29%29%29%29%3Bc0%3D%5B10000+10+0.01%5D%3B%5Bc%2Cresnorm%5D%3Dlsqcurve)
Matlab Lsqucurvefit 函数 “Function value and YDATA sizes are not equal”clear all;clc;x=[35000 45000 55000];y=[0.5646 0.7374 0.8743];f=@(c,x)(c(2)*x.^c(3)*sin(pi/2*c(3))/(c(1)+c(2)*x.^c(3)*cos(pi/2*c(3))));c0=[10000 10 0.01];[c,resnorm]=lsqcurve
Matlab Lsqucurvefit 函数 “Function value and YDATA sizes are not equal”
clear all;clc;
x=[35000 45000 55000];
y=[0.5646 0.7374 0.8743];
f=@(c,x)(c(2)*x.^c(3)*sin(pi/2*c(3))/(c(1)+c(2)*x.^c(3)*cos(pi/2*c(3))));
c0=[10000 10 0.01];
[c,resnorm]=lsqcurvefit(f,c0,x,y)
plot(x,y,'.-',x,f(c,x),'r:x')
legend('原始数据','拟合数据')
Matlab Lsqucurvefit 函数 “Function value and YDATA sizes are not equal”clear all;clc;x=[35000 45000 55000];y=[0.5646 0.7374 0.8743];f=@(c,x)(c(2)*x.^c(3)*sin(pi/2*c(3))/(c(1)+c(2)*x.^c(3)*cos(pi/2*c(3))));c0=[10000 10 0.01];[c,resnorm]=lsqcurve
clear all;
clc;
x=[35000 45000 55000];
y=[0.5646 0.7374 0.8743];
f=@(c,x)(c(2)*x.^c(3)*sin(pi/2*c(3))./(c(1)+c(2)*x.^c(3)*cos(pi/2*c(3))));%注意这一行要用点除
c0=[10000 10 0.01];
[c,resnorm]=lsqcurvefit(f,c0,x,y)
plot(x,y,'.-',x,f(c,x),'r:x')
legend('原始数据','拟合数据')
结果:
Optimization terminated: first-order optimality less than OPTIONS.TolFun,
and no negative/zero curvature detected in trust region model.
c =
1.0e+003 *
10.0000 0.0300 0.0104
resnorm =
0.0482
点太少了