The parameter dimension is not relevant for the peak filtering, since you can apply a lowpass filter in any dimension. But the training method is. It is only implemented for Ascent and brute force, not for Genetic. For implementing your own algorithm, look in the manual for the parameters() function.
Thanks for the info. When looking into the parameters() function, I understand that it allows me to customize the parameter list which is evaluated at each optimization iteration, however what I am interested is in applying my own algorithm to the full list of results calculated through brute force. Is there any built in function which I can modify to do that, or would I need to manually do it after the optimize loop is completed?
Thanks
