  Discrete-time systems under aperiodic sampling may serve as a modeling
abstraction for a multitude of problems arising in cyber-physical and networked
control systems. Recently, model- and data-based stability conditions for such
systems were obtained by rewriting them as an interconnection of a linear
time-invariant system and a delay operator, and subsequently, performing a
robust stability analysis using a known bound on the gain of this operator. In
this paper, we refine this approach: First, we show that the delay operator is
input-feedforward passive and second, we compute its gain exactly. Based on
these findings, we derive improved stability conditions both in case of full
model knowledge and in case only data are available. In the latter, we require
only a finite-length and potentially noisy state-input trajectory of the
unknown system. In two examples, we illustrate the reduced conservativeness of
the proposed stability conditions over existing ones.
