A class of cellular automata modeling winnerless competition
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Neural units introduced by Rabinovich et al. (Sensory coding with dynamically competitive networks, UCSD and CIT, February 1999) motivate a class of cellular automata (CA) where spatio-temporal encoding is feasible. The spatio-temporal information capacity of a CA is estimated by the information capacity of the attractor set, which happens to be finitely specified. Two-dimensional CA are studied in detail. An example is given for which the attractor is not a subshift. © 2002 American Institute of Physics.
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