Abstract
A cellular automaton is a discrete dynamic system of simple construction, yet capable of exhibiting complex self-organizing behavior. A cellular automaton can be used to model differential systems by assuming that time and space are quantized, and that the dependent variable takes on a finite set of possible values. Cellular-automaton behavior falls into four distinct universality classes, analogous to (1) limit points, (2) limit cycles, (3) chaotic attractors (fractals), and (4) 'universal computers'. The behavior of members of each of these four classes is explored in the context of digital spectral filtering. The utility of class 2 behavior in experimental data analysis is demonstrated with a laboratory example.
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