Abstract
Cellular automata are arrays of processing elements which operate in a synchronous, parallel fashion and can be used to process or classify their arrays of input data. This chapter summarizes work done over the past few years at the University of Maryland on generalizations of the basic cellular automaton concept. It shows how the speed and power of cellular automata can be increased by extending the array into an appropriately connected larger structure or by allowing the individual processors to have larger amounts of internal memory. It also extends the cellular automaton concept to networks of processors in which each node has bounded degree and discusses the graph processing and recognition capabilities of such networks.
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References
Dyer, C. R., “Augmented Cellular Automata for Image Analysis,” Ph.D. Dissertation, University of Maryland, College Park (1979).
Dyer, C. R., and Rosenfeld, A., “Parallel Image Processing by Memory Augmented Cellular Automata,” IEEETPAMI (1980) (in press).
Rosenfeld, A., Picture Languages, New York, Academic Press (1979).
Wu, A. Y., “Cellular Graph Automata,” Ph.D. Dissertation, University of Maryland, College Park (1978).
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Wu, A., and Rosenfeld, A., “Sequential and Cellular Graph Automata,” Info. Sciences 20:57–68 (1980).
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© 1981 Plenum Press, New York
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Rosenfeld, A. (1981). Generalized Cellular Automata. In: Onoe, M., Preston, K., Rosenfeld, A. (eds) Real-Time Parallel Computing. Springer, Boston, MA. https://doi.org/10.1007/978-1-4684-3893-2_4
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DOI: https://doi.org/10.1007/978-1-4684-3893-2_4
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4684-3895-6
Online ISBN: 978-1-4684-3893-2
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