Cellular-Automaton Profiling of Acoustic Data for Feature Extraction of Turbulent Flow in Occluded Carotid Arteries

The Greenberg-Hastings cellular automaton can be used to create feature-rich profiles of the complex waveform data caused by turbulent blood-flow in an occluded carotid artery if it is combined with recent work in differential calculus and approximation theory relating to boolean functions. We show how to undertake the derivation of a Maclaurin power series representation of the Greenberg-Hastings rule and combine this with an information theoretic approach designed to make use of ambient noise rather than treat it as a nuisance. We discuss the preliminary results of applying the technique to sound recordings taken from physical simulations of occluded carotid arteries.