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New properties of 2D Cellular Automata found through Polynomial Cellular Neural Networks

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2 Author(s)
Pazienza, G.E. ; Cellular Sensory Wave Comput. Lab., MTA - SZTAKI, Budapest, Hungary ; Gomez-Ramirez, E.

In this paper we show how polynomial cellular neural networks can be used to find new properties of two-dimensional binary cellular automata (CA). In particular, we define formally a complexity index for totalistic and semi-totalistic CA, and we discuss on the intrinsic complexity of universal CA finding a surprising result: universal rules are slightly more complex than linearly separable ones.

Published in:

Neural Networks, 2009. IJCNN 2009. International Joint Conference on

Date of Conference:

14-19 June 2009