  Negation operation is important in intelligent information processing.
Different with existing arithmetic negation, an exponential negation is
presented in this paper. The new negation can be seen as a kind of geometry
negation. Some basic properties of the proposed negation is investigated, we
find that the fix point is the uniform probability distribution. The negation
is an entropy increase operation and all the probability distributions will
converge to the uniform distribution after multiple negation iterations. The
number of iterations of convergence is inversely proportional to the number of
elements in the distribution. Some numerical examples are used to illustrate
the efficiency of the proposed negation.
