Applications of cellular automata: attractors and fractals in analytical chemistry?

Robert A. Lodder; Gary M. Hieftje; Mark Selby

doi:10.1016/0165-9936(88)85071-4

Applications of cellular automata: attractors and fractals in analytical chemistry?

Robert A. Lodder, Gary M. Hieftje, Mark Selby

Research output: Contribution to journal › Short survey › peer-review

2 Scopus citations

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.

Original language	English
Pages (from-to)	240-244
Number of pages	5
Journal	TrAC - Trends in Analytical Chemistry
Volume	7
Issue number	7
DOIs	https://doi.org/10.1016/0165-9936(88)85071-4
State	Published - Aug 1988

Bibliographical note

Funding Information:
Acknowledgements This work hasb eens upportedi n part by the National Science Foundation through Grant CHE 87-

Funding

Acknowledgements This work hasb eens upportedi n part by the National Science Foundation through Grant CHE 87-

Funders	Funder number
National Science Foundation (NSF)	CHE 87-

ASJC Scopus subject areas

Analytical Chemistry
Spectroscopy

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title = "Applications of cellular automata: attractors and fractals in analytical chemistry?",

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.",

author = "Lodder, {Robert A.} and Hieftje, {Gary M.} and Mark Selby",

note = "Funding Information: Acknowledgements This work hasb eens upportedi n part by the National Science Foundation through Grant CHE 87-",

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language = "English",

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T2 - attractors and fractals in analytical chemistry?

AU - Lodder, Robert A.

AU - Hieftje, Gary M.

AU - Selby, Mark

N1 - Funding Information: Acknowledgements This work hasb eens upportedi n part by the National Science Foundation through Grant CHE 87-

PY - 1988/8

Y1 - 1988/8

N2 - 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.

AB - 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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Applications of cellular automata: attractors and fractals in analytical chemistry?

Abstract

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