A new kind of science
On the rectangular grid representation of general CNN networks: Research Articles
International Journal of Circuit Theory and Applications - CNN Technology
Polynomial cellular neural networks for implementing the game of life
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Computing the Weights of Polynomial Cellular Neural Networks Using Quadratic Programming
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
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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 semitotalistic 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.