  A very simple heuristic approach to the unfolding problem will be described.
An iterative algorithm starts with an empty histogram and every iteration aims
to add one entry to this histogram. The entry to be added is selected according
to a criteria which includes a $\chi^2$ test and a regularization. After a
relatively small number of iterations (500 - 1000) the growing reconstructed
distribution converges to the true distribution.
