  This article is concerned with data-driven analysis of discrete-time systems
under aperiodic sampling, and in particular with a data-driven estimation of
the maximum sampling interval (MSI). The MSI is relevant for analysis of and
controller design for cyber-physical, embedded and networked systems, since it
gives a limit on the time span between sampling instants such that stability is
guaranteed. We propose tools to compute the MSI for a given controller and to
design a controller with a preferably large MSI, both directly from a
finite-length, noise-corrupted state-input trajectory of the system. We follow
two distinct approaches for stability analysis, one taking a robust control
perspective and the other a switched systems perspective on the aperiodically
sampled system. In a numerical example and a subsequent discussion, we
demonstrate the efficacy of our developed tools and compare the two approaches.
