MATLAB: Exponential Linear Regression fitting model

esponentialfitting datalinear regression

Hi everyone,

I'd like to have an help to resolve the following problem,

I have this relationship Y=b*exp(-a/x), I know the values of Y and x, but I need to find the values of a and b. Can I use the linear regression model (polyfit/polyval)? In case it is possible, how can I use it?

Thank you,

Matteo

Best Answer

Take LOG on both sides:

LOG(Y)=LOG(b)-a/x.

Then fit LOG(Y) against 1/x using polyfit for a polynomial of degree 1.

Alternatively, use lsqcurvefit to fit the data to the original model (the results for a and b for both approaches will differ).

Best wishes

Torsten.

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MATLAB: How to do a linear fit with forced slope

If your data are column vectors x and y and your model is

y=m*x+b

then the solution for b would simply be

b_fit = mean(y-m*x);

MATLAB: Fitting exponential

I will assume that you have the 15,000 data samples stored in the MATLAB Workspace as a 15,000 x 1 column vector called dataset.x.

   %%Create time domain:
   N = size(dataset.x,1);
   Fs = 125;
   dt = 1/Fs;
   dataset.t = dt*(0:N-1)';
   %%Create subset:
   p = 600;
   q = 200;
   subset.x = [  dataset.x(1:p) ;  dataset.x(end-q+1:end)  ];
   subset.t = [  dataset.t(1:p) ;  dataset.t(end-q+1:end)  ];
   %%Exponential fit:
   fitType = 'exp1';
   myFit = fit(subset.t,subset.x,fitType);

HTH.

Rick

Best Answer

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