"fsalehi " <firstname.lastname@example.org> wrote in message <email@example.com>... > spasmous <firstname.lastname@example.org> wrote in message <email@example.com>... > > On Aug 30, 12:34 am, "fsalehi " <fsal...@gmail.com> wrote: > > > I have a problem with 'lsqnonlin' function in matlab. I used it to optimizing this function: > > > > > > objfun = @(z) y - ( z(5).*exp(-z(1).*(t-z(7)).^2).*cos(2*pi.*z(2).*(t-z(7))+z(3)) + z(6).*exp(-z(1).*(t-z(8)).^2).*cos(2*pi.*z(2).*(t-z(8))+z(4)) ); > > > > > > % y is my signal and I optimize a guassian pulse function for Model Base Estimation > > > > > > options = optimset(options, 'MaxFunEvals', 10000, 'TolX', 1e-3, 'TolFun', 1e-2, 'MaxIter', 800, 'LargeScale', 'on', 'LevenbergMarquardt', 'on', 'DiffMaxChange', 1e-7, 'DiffMinChange', 1e-10, 'Display', 'off', 'Diagnostics', 'off'); > > > > > > > i would try Display 'iter' to see what is happening. TolFun seems kind > > of large and DiffMaxChange kind of small. Aslo I'm not sure > > LargeScale, LevMarq and bound constraints are all compatible either. > > I'm not sure too. but I dont know what setting I should use?
Regarding the LargeScale and LevenbergMarquardt settings, lsqnonlin will run the LargeScale (a.k.a. trust-region-reflective) algorithm since the parameters are constrained by bounds. This is not an issue.
I agree about the DiffMaxChange being too small. When your parameter (alpha) is on the scale of 1e13, then a difference of 1e-7 will be far too small to get an accurate finite-difference derivative estimate. What might be happening is that the derivative estimate for the first parameter may appear flat:
>> (1e13+1e-7) - 1e13 ans =
Try scaling the alpha parameter to be the same scale as the other parameters. Unfortunately, DiffMaxChange and DiffMinChange are one-size fits all options so increasing DiffMaxChange to a larger value may negatively affect your other parameters.