  We consider the problem of impulse response estimation of stable linear
single-input single-output systems. It is a well-studied problem where flexible
non-parametric models recently offered a leap in performance compared to the
classical finite-dimensional model structures. Inspired by this development and
the success of deep learning we propose a new flexible data-driven model. Our
experiments indicate that the new model is capable of exploiting even more of
the hidden patterns that are present in the input-output data as compared to
the non-parametric models.
