  We present some forms of uncertainty principle which involve in a new way
localization operators, the concept of $\varepsilon$-concentration and the
standard deviation of $L^2$ functions. We show how our results improve the
classical Donoho-Stark estimate in two different aspects: a better general
lower bound and a lower bound in dependence on the signal itself.
