Sampling of deterministic signals and systems

In this paper, we analyze sampling approximations of stable linear time-invariant systems for input signals in the Paley-Wiener space PW _π¹. The goal is to approximate a transform Tf by using only the samples of the signal f, which do not necessarily have to be equidistant. We completely characterize the stable linear time-invariant (LTI) systems T and sampling patterns for which the approximation process converges to Tf for all signals in PW_π¹. Furthermore, we prove that for every complete interpolating sequence there exist a stable LTI system and a signal in PW_π¹ for which the approximation error increases unboundedly as the number of samples that are used for the approximation is increased. This shows that a more flexible choice of the sampling points instead of equidistant sampling, where such a divergence behavior is known to exist, is not sufficient to overcome the divergence. Thus, sampling based signal processing has fundamental limits. The calculations further indicate that oversampling cannot resolve the convergence problems.