  A kernel based procedure for correcting experimental data for distortions due
to the finite resolution and limited detector acceptance is presented. The
unfolding problem is known to be an ill-posed problem that can not be solved
without some a priori information about solution such as, for example,
smoothness or positivity. In the approach presented here the true distribution
is estimated by a weighted sum of kernels, with the width of the kernels acting
as a regularization parameter responsible for the smoothness of the result.
Cross-validation is used to determine an optimal value for this parameter. A
numerical example with a simulation study of systematical and statistical
errors is presented to illustrate the procedure.
