  In the remote state estimation problem, an observer tries to reconstruct the
state of a dynamical system at a remote location, where no direct sensor
measurements are available. The observer only has access to information sent
through a digital communication channel with a finite capacity. The recently
introduced notion of restoration entropy provides a way to determine the
smallest channel capacity above which an observer can be designed that observes
the system without a degradation of the initial observation quality. In this
paper, we propose a subgradient algorithm to estimate the restoration entropy
via the computation of an appropriate Riemannian metric on the state space,
which allows to determine the approximate value of the entropy from the
time-one map (in the discrete-time case) or the generating vector field (for
ODE systems), respectively.
