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.

翻译：数字信号理论是对连续信号分析的扩展，这一扩展通过离散化和采样实现。信号的采样在数学上可用一系列狄拉克脉冲描述，且已为人熟知。狄拉克脉冲的采样等性质源于分布理论。该理论将微分学推广至经典意义上不可微的函数（如赫维赛德阶跃函数）。因此，分布理论允许将模拟分析方法应用于数字信号。在本报告中，我们将信号理论中已知的狄拉克梳（一系列狄拉克脉冲）概念扩展至计算机性能分析。目标是建立电气工程或物理学方法与不同计算模型（如图、网络及实时演算）之间的联系。