On the Rate of Information Loss in Memoryless Systems

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.