Global fitting of multiple data sets simultaneously using a nonlinear least squares fit.

I have a rather large data matrix with a size of 19x17. The points within this matrix correspond to the absorbance of a specific wave number at a specific time(x=wave number, y=time). I am trying to apply a global Gaussian fit to the data within the matrix where there are two local maxima. I would like to use the following equation to fit the data: Abs(t)=sum(Amax1*exp(-0.5((x-vmax1)/s1)^2))+Amax2*exp(-0.5((x-vmax2)/s2)^2))), where vmax1 and vmax2 correspond to the wave number of each maxima (these values are constant for all calculations and all data sets), Amax1 and Amax2 correspond to the maximum absorbance of each of the maxima wave numbers (this valuable is varied over multiple all data sets), and s1 and s2 correspond to the width of the Gaussian curve (this is also varied). Is there a way to apply a nonlinear least fit of the entire data matrix for this Gaussian fit? Thank you in advance!