% -*- texinfo -*-
% @deftypefn {Function File} {} mutualinformation (@var{xy})
%
% Computes the mutual information of the given channel transition matrix.
% By definition we have @code{I(@var{x}, @var{y})} given as
% @code{I(@var{x}:@var{y}) = SUM(P(@var{x},@var{y}) * log2(p(@var{x},@var{y})
% / p(@var{x})/p(@var{y}))) = relative_entropy(P(@var{x},@var{y}) |
% P(@var{x}),P(@var{y}))}
% Mutual Information, is amount of information, one variable
% has, about the other. It is the reduction of uncertainity.
% This is a symmetric function.
% @seealso{entropy, conditionalentropy}
% @end deftypefn