  In this paper, we consider the problem of recovery of a burst-like forcing
term in an initial value problem (IVP) in the framework of dynamical sampling.
We introduce an idea of using two particular classes of samplers that allow one
to predict the solution of the IVP over a time interval without a burst. This
leads to two different algorithms that stably and accurately approximate the
burst-like forcing term even in the presence of a measurement acquisition error
and a large background source.
