% -*- texinfo -*-
% @deftypefn {Function File} {}[@var{net}] = train (@var{MLPnet},@var{mInputN},@var{mOutput},@var{[]},@var{[]},@var{VV})
% A neural feed-forward network will be trained with @code{train}
%
% @example
% [net,tr,out,E] = train(MLPnet,mInputN,mOutput,[],[],VV);
% @end example
% @noindent
%
% left side arguments:
% @example
% net: the trained network of the net structure @code{MLPnet}
% tr :
% out:
% E : Error
% @end example
% @noindent
%
% right side arguments:
% @example
% MLPnet : the untrained network, created with @code{newff}
% mInputN: normalized input matrix
% mOutput: output matrix (normalized or not)
% [] : unused parameter
% [] : unused parameter
% VV : validize structure
% @end example
% @end deftypefn