# Can I run a GA to optimize wavelet transform?

I am running a wavelet transform (cmor) to estimate damping and frequencies that exists in a signal.cmor has 2 parameters that I can change them to get more accurate results. center frequency(Fc) and bandwidth frequency(Fb). If I construct a signal with few freqs and damping then I can measure the error of my estimation(fig 2). but in actual case I have a signal and I don't know its freqs and dampings so I can't measure the error.so a friend in here suggested me to reconstruct the signal and find error by measuring the difference between the original and reconstructed signal e(t)=|x(t)−x^(t)|. so my question is:
Does anyone know a better function to find the error between reconstructed and original signal,rather than e(t)=|x(t)−x^(t)|.
can I use GA to search for Fb and Fc? or do you know a better search method?
Hope this picture shows what I mean, the actual case is last one. others are for explanations

• I think GA is not a suitable optimization algorithm for this problem. GA is mostly used when parameters to be optimized are a lot and when the objective function varies in a way which is not able to be tracked. I suggest you to use Wavelets with high accuracy. Sep 1, 2013 at 19:18
• @MahdiKhosravi hi, thanks for your answer. what is " Wavelets with high accuracy"? a new wavelet type or what?
– SAH
Sep 1, 2013 at 19:55
• I mean use Wavelets with higher resolution to get results with more accuracy. Sep 1, 2013 at 20:35
• @MahdiKhosravi I've done that already and the estimated parameters are accurate enough.But in this post I wanted to ask how can I optimize fc and fb(resolution) with another algorithm.
– SAH
Sep 2, 2013 at 7:28
• $e(t) = |x(t) - \hat x(t)|$. I don't have any better idea. Sep 2, 2013 at 13:08