  In this work we present results about the rate of (relative) information loss
induced by passing a real-valued, stationary stochastic process through a
memoryless system. We show that for a special class of systems the information
loss rate is closely related to the difference of differential entropy rates of
the input and output processes. It is further shown that the rate of (relative)
information loss is bounded from above by the (relative) information loss the
system induces on a random variable distributed according to the process's
marginal distribution.
  As a side result, in this work we present sufficient conditions such that for
a continuous-valued Markovian input process also the output process possesses
the Markov property.
