如何在Matlab里对曲线y=exp(-k*X^N)的拟合?x = [0:8:112];y = [64.66,61.56,58.59,50.42,48.56,45.83,42.61,40.01,37.16,34.99,33.14,31.71,30.60,29.98,29.17];数据y=[1 0.95210728 0.906130268 0.779693487 0.75095785 0.708812 0.659004 0.618774 0.5747

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如何在Matlab里对曲线y=exp(-k*X^N)的拟合?x=[0:8:112];y=[64.66,61.56,58.59,50.42,48.56,45.83,42.61,40.01,37.16,3

如何在Matlab里对曲线y=exp(-k*X^N)的拟合?x = [0:8:112];y = [64.66,61.56,58.59,50.42,48.56,45.83,42.61,40.01,37.16,34.99,33.14,31.71,30.60,29.98,29.17];数据y=[1 0.95210728 0.906130268 0.779693487 0.75095785 0.708812 0.659004 0.618774 0.5747
如何在Matlab里对曲线y=exp(-k*X^N)的拟合?
x = [0:8:112];
y = [64.66,61.56,58.59,50.42,48.56,45.83,42.61,40.01,37.16,34.99,33.14,31.71,30.60,29.98,29.17];
数据y=[1 0.95210728 0.906130268 0.779693487 0.75095785 0.708812 0.659004 0.618774 0.574713 0.541188 0.512452 0.490421 0.47318 0.463602 0.451149 ]

如何在Matlab里对曲线y=exp(-k*X^N)的拟合?x = [0:8:112];y = [64.66,61.56,58.59,50.42,48.56,45.83,42.61,40.01,37.16,34.99,33.14,31.71,30.60,29.98,29.17];数据y=[1 0.95210728 0.906130268 0.779693487 0.75095785 0.708812 0.659004 0.618774 0.5747

1.你这个数据显然不能用y=exp(-k*X^N)去拟合

当x=0时y=exp(-k*X^N)=1,而你给的第一个y值是64.66,这错的太离谱了!

2.用y=a*exp(-b*x^c)是可以的

General model:

       f(x) = a*exp(-b*x^c)

Coefficients (with 95% confidence bounds):

       a =       66.01  (63.28, 68.75)

       b =     0.01589  (0.006259, 0.02552)

       c =      0.8514  (0.7225, 0.9803)

Goodness of fit:

  SSE: 22.64

  R-square: 0.9887

  Adjusted R-square: 0.9868

  RMSE: 1.374

 

 

 


 

 

 

 

能否将
y=exp(-k*X^N)
改为
y=a*exp(-b*x^c)

polyfit

你这不能用ployfit拟合，那是拟合线性曲线的，要用lsqcurvefit，lsqcurvefit是拟合指数函数的！

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