How to perform this Complex Exponential Fitting?
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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!
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the cyclist
am 21 Jul. 2015
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.
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