  We develop a new model selection method for the adaptive robust efficient
nonparametric signal estimation observed with impulse noise which is defined by
the general non Gaussian L\'evy processes. On the basis of the developed
method, we construct the estimation procedures which are analyzed in two
settings: in non asymptotic and asymptotic ones. For the first time for such
models we show non asymptotic sharp oracle inequalities for the quadratic and
for the robust risks, i.e. we show that the constructed procedures are optimal
in the sharp oracle inequalities sense. Next, by making use of the obtained
oracle inequalities, we provide the asymptotic efficiency property for the
developed estimation methods in the adaptive setting when the signal/noise
ratio goes to infinity. We apply the developed model selection methods for the
signals number detection problem in multi-path information transmission.
