How to perform this Complex Exponential Fitting?

Experiment result can be represented as a sum of damped exponential, sum over 1..k.

y(n)=sum(a(k)*exp(-(d(k)+j*w(k))*n+j*p(k))

The experimental result, y, is vector from 1..n;

a, d, w, p are parameters to fit, k sets; total parameters to fit are 4*k (or an array of [4 k]);

Only initial k values of "w" can be known a-prior pretty accurately;

How to write a code to do this fitting?

Thanks in advance!

Answer 1

[the cyclist]

If you have the Statistics and Machine Learning Toolbox, then you should be able to use the nlinfit function to do this type of fit.