Quote:
Originally Posted by Kais_M
is it possible to use G.D. to optimize a complex parameter vector? still linear model with mean square error measure, but the parameters are complex not real. I did some derivation, but not sure my derivatives wrt complex numbers are correct.. would like to hear from people here how they dealt (would deal) with this problem.
many thanks,

If the error function itself is realvalued, then this can be done by considering every complex parameter as two parameters (real and imaginary parts) and carrying out GD with respect to these (twice as many) real parameters. If the error function is complex, then there needs to be a definition of what the objective is since a "minimum complex number" is not a welldefined notion.