  In this work, we study minimum data rate tracking of a dynamical system under
a neuromorphic event-based sensing paradigm. We begin by bridging the gap
between continuous-time (CT) system dynamics and information theory's causal
rate distortion theory. We motivate the use of non-singular source codes to
quantify bitrates in event-based sampling schemes. This permits an analysis of
minimum bitrate event-based tracking using tools already established in the
control and information theory literature. We derive novel, nontrivial lower
bounds to event-based sensing, and compare the lower bound with the performance
of well-known schemes in the established literature.
