  Digital signal theory is an extension of the analysis of continuous signals.
This extension is provided by discretization and sampling. The sampling of
signals can be mathematically described by a series of Dirac impulses and is
well known. Properties of the Dirac impulse, such as sampling, are derived in
distribution theory. The theory generalizes differential calculus to functions
that are not differentiable in the classical sense such as the Heaviside step
function. Therefore, distribution theory allows one to adopt analog analysis
concepts to digital signals. In this report, we extend the concept of Dirac
combs, a series of Dirac impulses as known from signal theory, to performance
analysis of computers. The goal is to connect methods from electrical
engineering or physics to different models of computation such as graphs, and
network as well as real-time calculus.
