  There are numerous examples of natural and artificial processes that
represent stochastic sequences of events followed by an absolute refractory
period during which the occurrence of a subsequent event is impossible. In the
simplest case of a generalized Bernoulli scheme for uniform random events
followed by the absolute refractory period, the event probability as a function
of time can exhibit damped transient oscillations. Using stochastically-spiking
point neuron as a model example, we present an exact and compact analytical
description for the oscillations without invoking the standard renewal theory.
The resulting formulas stand out for their relative simplicity, allowing one to
analytically obtain the amplitude damping of the 2nd and 3rd peaks of the event
probability.
