[Kais_M]

thank you for the quick reply. I am using a real error measure, sum of squared errors, but it is a function of complex parameters. When deriving the equations for the error and the update rule for gradient descent you will hit a point -unless I'm making the same mistake every time- where you have to compute the derivative wrt a complex parameter. I do not have any intuition into that... seems that Dr Yaser is saying that you have to look at the complex parameter as a 2D vector of real numbers and compute derivative wrt that vector.. this why the # of parameters doubles. is this an "engineering" solution?? or is it really mathematically correct.. there seems to be much more to this than meets the eye..