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Journal articles on the topic 'Cellular automata'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Mardiris, Vassilios A., Georgios Ch Sirakoulis, and Ioannis G. Karafyllidis. "Automated Design Architecture for 1-D Cellular Automata Using Quantum Cellular Automata." IEEE Transactions on Computers 64, no. 9 (2015): 2476–89. http://dx.doi.org/10.1109/tc.2014.2366745.

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2

Jung, Goeun, and Youngho Kim. "Modeling of Spatio-temporal changes of Urban Sprawl in Jeju-island: Using CA (Cellular Automata) and ARD (Automatic Rule Detection)." Journal of the Association of Korean Geographers 10, no. 1 (2021): 139–52. http://dx.doi.org/10.25202/jakg.10.1.9.

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3

Hasanzadeh Mofrad, Mohammad, Sana Sadeghi, Alireza Rezvanian, and Mohammad Reza Meybodi. "Cellular edge detection: Combining cellular automata and cellular learning automata." AEU - International Journal of Electronics and Communications 69, no. 9 (2015): 1282–90. http://dx.doi.org/10.1016/j.aeue.2015.05.010.

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4

Bhardwaj, Rupali, and Anil Upadhyay. "Cellular Automata." Journal of Organizational and End User Computing 29, no. 1 (2017): 42–50. http://dx.doi.org/10.4018/joeuc.2017010103.

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Cellular automata (CA) are discrete dynamical systems consist of a regular finite grid of cell; each cell encapsulating an equal portion of the state, and arranged spatially in a regular fashion to form an n-dimensional lattice. A cellular automata is like computers, data represented by initial configurations which is processed by time evolution to produce output. This paper is an empirical study of elementary cellular automata which includes concepts of rule equivalence, evolution of cellular automata and classification of cellular automata. In addition, explanation of behaviour of cellular a

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5

Bandini, S. "Cellular automata." Future Generation Computer Systems 18, no. 7 (2002): v—vi. http://dx.doi.org/10.1016/s0167-739x(02)00067-5.

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6

Kutrib, Martin, Roland Vollmar, and Thomas Worsch. "Cellular automata." Parallel Computing 23, no. 11 (1997): 1565. http://dx.doi.org/10.1016/s0167-8191(97)82081-9.

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7

Schöfisch, B., and K. P. Hadeler. "Dimer automata and cellular automata." Physica D: Nonlinear Phenomena 94, no. 4 (1996): 188–204. http://dx.doi.org/10.1016/0167-2789(96)00039-5.

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8

Dennunzio, Alberto, Pierre Guillon, and Benoît Masson. "Sand automata as cellular automata." Theoretical Computer Science 410, no. 38-40 (2009): 3962–74. http://dx.doi.org/10.1016/j.tcs.2009.06.016.

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9

Allouche, J. P., F. V. Haeseler, E. Lange, A. Petersen, and G. Skordev. "Linear cellular automata and automatic sequences." Parallel Computing 23, no. 11 (1997): 1577–92. http://dx.doi.org/10.1016/s0167-8191(97)00074-4.

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10

Sutner, Klaus. "Linear cellular automata and Fischer automata." Parallel Computing 23, no. 11 (1997): 1613–34. http://dx.doi.org/10.1016/s0167-8191(97)00080-x.

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11

Pighizzini, Giovanni. "Asynchronous automata versus asynchronous cellular automata." Theoretical Computer Science 132, no. 1-2 (1994): 179–207. http://dx.doi.org/10.1016/0304-3975(94)90232-1.

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12

OKAYAMA, Tsuyoshi, and Haruhiko MURASE. "Leaf Cellular Automata." Shokubutsu Kojo Gakkaishi 14, no. 3 (2002): 152–56. http://dx.doi.org/10.2525/jshita.14.152.

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13

Beros, Achilles, Monique Chyba, and Oleksandr Markovichenko. "Controlled cellular automata." Networks & Heterogeneous Media 14, no. 1 (2019): 1–22. http://dx.doi.org/10.3934/nhm.2019001.

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14

Bolognesi, Tommaso, and Vincenzo Ciancia. "Nominal Cellular Automata." Electronic Proceedings in Theoretical Computer Science 223 (August 10, 2016): 24–35. http://dx.doi.org/10.4204/eptcs.223.2.

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15

BOCCARA, NINO. "RANDOMIZED CELLULAR AUTOMATA." International Journal of Modern Physics C 18, no. 08 (2007): 1303–12. http://dx.doi.org/10.1142/s0129183107011339.

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We define and study a few properties of a class of random automata networks. While regular finite one-dimensional cellular automata are defined on periodic lattices, these automata networks, called randomized cellular automata, are defined on random directed graphs with constant out-degrees and evolve according to cellular automaton rules. For some families of rules, a few typical a priori unexpected results are presented.

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16

Nobe, Atsushi, and Fumitaka Yura. "Linearizable cellular automata." Journal of Physics A: Mathematical and Theoretical 40, no. 26 (2007): 7159–74. http://dx.doi.org/10.1088/1751-8113/40/26/004.

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17

Agapie, Alexandru, Anca Andreica, and Marius Giuclea. "Probabilistic Cellular Automata." Journal of Computational Biology 21, no. 9 (2014): 699–708. http://dx.doi.org/10.1089/cmb.2014.0074.

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18

Mayer, Gary R., and Hessam S. Sarjoughian. "Composable Cellular Automata." SIMULATION 85, no. 11-12 (2009): 735–49. http://dx.doi.org/10.1177/0037549709106341.

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19

Stauffer, Dietrich. "Programming Cellular Automata." Computers in Physics 5, no. 1 (1991): 62. http://dx.doi.org/10.1063/1.4822970.

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20

Maddox, John. "Mechanizing cellular automata." Nature 321, no. 6066 (1986): 107. http://dx.doi.org/10.1038/321107a0.

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21

Lent, C. S., P. D. Tougaw, W. Porod, and G. H. Bernstein. "Quantum cellular automata." Nanotechnology 4, no. 1 (1993): 49–57. http://dx.doi.org/10.1088/0957-4484/4/1/004.

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22

KOKOLAKIS, I., I. ANDREADIS, and PH TSALIDES. "PROGRAMMABLE CELLULAR AUTOMATA." Journal of Circuits, Systems and Computers 09, no. 05n06 (1999): 255–60. http://dx.doi.org/10.1142/s0218126699000219.

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A new architecture of the binary cellular automata (CA), called programmable CA (PCA), is presented for the first time in this letter. The basic properties of the PCA are also studied. The proposed architecture is simple and fast and aims at providing efficient solutions to a variety of CA applications.

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23

Kornyak, V. V. "Symmetric cellular automata." Programming and Computer Software 33, no. 2 (2007): 87–93. http://dx.doi.org/10.1134/s0361768807020065.

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24

Moore, Cristopher. "Quasilinear cellular automata." Physica D: Nonlinear Phenomena 103, no. 1-4 (1997): 100–132. http://dx.doi.org/10.1016/s0167-2789(96)00255-2.

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25

Fricke, Thomas. "Stochastic cellular automata." Nonlinear Analysis: Theory, Methods & Applications 30, no. 3 (1997): 1847–58. http://dx.doi.org/10.1016/s0362-546x(96)00378-1.

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26

Kutrib, Martin. "Pushdown cellular automata." Theoretical Computer Science 215, no. 1-2 (1999): 239–61. http://dx.doi.org/10.1016/s0304-3975(97)00187-4.

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27

Bandini, Stefania, and Giancarlo Mauri. "Multilayered cellular automata." Theoretical Computer Science 217, no. 1 (1999): 99–113. http://dx.doi.org/10.1016/s0304-3975(98)00152-2.

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28

Di Lena, Pietro, and Luciano Margara. "Nondeterministic Cellular Automata." Information Sciences 287 (December 2014): 13–25. http://dx.doi.org/10.1016/j.ins.2014.07.007.

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29

Jadur, Camilo, Masakazu Nasu, and Jorge Yazlle. "Permutation Cellular Automata." Acta Applicandae Mathematicae 126, no. 1 (2013): 203–43. http://dx.doi.org/10.1007/s10440-013-9814-7.

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30

Fokas, A. S., E. P. Papadopoulou, and Y. G. Saridakis. "Soliton cellular automata." Physica D: Nonlinear Phenomena 41, no. 3 (1990): 297–321. http://dx.doi.org/10.1016/0167-2789(90)90001-6.

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31

Montgomery, David, and Gary D. Doolen. "Magnetohydrodynamic cellular automata." Physics Letters A 120, no. 5 (1987): 229–31. http://dx.doi.org/10.1016/0375-9601(87)90214-3.

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32

Kaneko, Kunihiko. "Symplectic cellular automata." Physics Letters A 129, no. 1 (1988): 9–16. http://dx.doi.org/10.1016/0375-9601(88)90464-1.

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33

Toole, Jameson, and Scott E. Page. "Predicting Cellular Automata." Complex Systems 19, no. 4 (2010): 343–62. http://dx.doi.org/10.25088/complexsystems.19.4.343.

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34

Phan, Victor Duy. "Commutative Cellular Automata." Complex Systems 25, no. 1 (2016): 23–38. http://dx.doi.org/10.25088/complexsystems.25.1.23.

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35

Milošević, M. V., G. R. Berdiyorov, and F. M. Peeters. "Fluxonic cellular automata." Applied Physics Letters 91, no. 21 (2007): 212501. http://dx.doi.org/10.1063/1.2813047.

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36

Hatori, Tadatsugu. "Magnetohydrodynamic Cellular Automata." Progress of Theoretical Physics Supplement 99 (1989): 229–43. http://dx.doi.org/10.1143/ptps.99.229.

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37

Bruschi, M., P. M. Santini, and O. Ragnisco. "Integrable cellular automata." Physics Letters A 169, no. 3 (1992): 151–60. http://dx.doi.org/10.1016/0375-9601(92)90585-a.

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38

Jen, Erica. "Cylindrical cellular automata." Communications in Mathematical Physics 118, no. 4 (1988): 569–90. http://dx.doi.org/10.1007/bf01221109.

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39

Kari, Jarkko, Ville Salo, and Thomas Worsch. "Sequentializing cellular automata." Natural Computing 19, no. 4 (2019): 759–72. http://dx.doi.org/10.1007/s11047-019-09745-7.

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Abstract We study the problem of sequentializing a cellular automaton without introducing any intermediate states, and only performing reversible permutations on the tape. We give a decidable characterization of cellular automata which can be written as a single sweep of a bijective rule from left to right over an infinite tape. Such cellular automata are necessarily left-closing, and they move at least as much information to the left as they move information to the right.

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40

Takahashi, Satoshi. "Cellular automata and multifractals: Dimension spectra of linear cellular automata." Physica D: Nonlinear Phenomena 45, no. 1-3 (1990): 36–48. http://dx.doi.org/10.1016/0167-2789(90)90172-l.

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41

Adamatzky, Andrew. "Automatic programming of cellular automata: identification approach." Kybernetes 26, no. 2 (1997): 126–35. http://dx.doi.org/10.1108/03684929710163074.

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42

Calidonna, C. R., S. Di Gregorio, and M. Mango Furnari. "Mapping applications of cellular automata into applications of cellular automata networks." Computer Physics Communications 147, no. 1-2 (2002): 724–28. http://dx.doi.org/10.1016/s0010-4655(02)00385-5.

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43

Ruivo, Eurico L. P., and Pedro P. B. de Oliveira. "Inferring the Limit Behavior of Some Elementary Cellular Automata." International Journal of Bifurcation and Chaos 27, no. 08 (2017): 1730028. http://dx.doi.org/10.1142/s0218127417300282.

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Cellular automata locally define dynamical systems, discrete in space, time and in the state variables, capable of displaying arbitrarily complex global emergent behavior. One core question in the study of cellular automata refers to their limit behavior, that is, to the global dynamical features in an infinite time evolution. Previous works have shown that for finite time evolutions, the dynamics of one-dimensional cellular automata can be described by regular languages and, therefore, by finite automata. Such studies have shown the existence of growth patterns in the evolution of such finite

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44

BEIGY, HAMID, and M. R. MEYBODI. "OPEN SYNCHRONOUS CELLULAR LEARNING AUTOMATA." Advances in Complex Systems 10, no. 04 (2007): 527–56. http://dx.doi.org/10.1142/s0219525907001264.

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Cellular learning automata is a combination of learning automata and cellular automata. This model is superior to cellular learning automata because of its ability to learn and also is superior to single learning automaton because it is a collection of learning automata which can interact together. In some applications such as image processing, a type of cellular learning automata in which the action of each cell in the next stage of its evolution not only depends on the local environment (actions of its neighbors) but it also depends on the external environments. We call such a cellular learn

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45

Gavrilov, S. V., I. V. Matyushkin, and A. L. Stempkovsky. "Computability via Cellular Automata." Scientific and Technical Information Processing 44, no. 5 (2017): 314–28. http://dx.doi.org/10.3103/s0147688217050057.

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46

D’Ambrosio, Donato, Giuseppe Filippone, Rocco Rongo, William Spataro, and Giuseppe A. Trunfio. "Cellular Automata and GPGPU." International Journal of Grid and High Performance Computing 4, no. 3 (2012): 30–47. http://dx.doi.org/10.4018/jghpc.2012070102.

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This paper presents an efficient implementation of the SCIARA Cellular Automata computational model for simulating lava flows using the Compute Unified Device Architecture (CUDA) interface developed by NVIDIA and carried out on Graphical Processing Units (GPU). GPUs are specifically designated for efficiently processing graphic data sets. However, they are also recently being exploited for achieving excellent computational results for applications non-directly connected with Computer Graphics. The authors show an implementation of SCIARA and present results referred to a Tesla GPU computing pr

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47

Lobanov, Alexey I. "Model of cellular automata." Computer Research and Modeling 2, no. 3 (2010): 273–93. http://dx.doi.org/10.20537/2076-7633-2010-2-3-273-293.

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48

Bashkin, Vladimir A., and Irina A. Lomazova. "Cellular Resource-Driven Automata." Fundamenta Informaticae 120, no. 3-4 (2012): 243–57. http://dx.doi.org/10.3233/fi-2012-760.

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49

Tošic, Predrag T. "Cellular Automata Communication Models." International Journal of Natural Computing Research 1, no. 3 (2010): 66–84. http://dx.doi.org/10.4018/jncr.2010070105.

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In this paper, cellular automata (CA) are viewed as an abstract model for distributed computing. The author argues that the classical CA model must be modified in several important respects to become a relevant model for large-scale MAS. The paper first proposes sequential cellular automata (SCA) and formalizes deterministic and nondeterministic versions of SCA. The author then analyzes differences in possible dynamics between classical parallel CA and various SCA models. The analysis in this paper focuses on one-dimensional parallel and sequential CA with node update rules restricted to simpl

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50

Ollinger, Nicolas. "Intrinsically Universal Cellular Automata." Electronic Proceedings in Theoretical Computer Science 1 (June 25, 2009): 199–204. http://dx.doi.org/10.4204/eptcs.1.19.

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