2007
Seck-Tuoh-Mora, J.C., González-Hernández, M., Hernández-Romero, N., Rodríguez-Trejo, A., & Chapa-Vergara, S. V. (2007). Modeling linear dynamical systems by continuous-valued cellular automata. International Journal of Modern Physics C, 18(5), 833-848.
Abstract
This paper exposes a procedure for modeling and solving linear systems using continuous-valued cellular automata. The original part of this work consists on showing how the cells in the automaton may contain both real values and operators for carrying out numerical calculations and solve a desired problem. In this sense the automaton acts as a program, where data and operators are mixed in the evolution space for obtaining the correct calculations. As an example, Euler's integration method is implemented in the configuration space in order to achieve an approximated solution for a dynamical system. Three examples showing linear behaviors are presented.
How to Make Dull Cellular Automata Complex by Adding Memory: Rule 126 Case Study
Unconventional invertible behaviors in reversible one-dimensional cellular automata.
Modeling a Nonlinear Liquid Level System by Cellular Neural Networks
Reproducing the Cyclic Tag System Developed by Matthew Cook with Rule 110 Using the Phases f(i-)1.
Elementary cellular automaton Rule 110 explained as a block substitution system
Complex Dynamics Emerging in Rule 30 with Majority Memory
Pair Diagram and Cyclic Properties Characterizing the Inverse of Reversible Automata