Parallel computation of fractal sets with the help of neural networks and cellular automata
Fractal sets of a broad class are described by Deterministic Iterated Function Systems. It has been shown by J. Stark that one can build a binary asymmetric Neural Network whose attractor gives an approximation of the corresponding fractal set. The author of the article has suggested a version of the Neural Network Algorithm which is more convenient and efficient in some cases. Here we show a way of going from Deterministic Iterated Function Systems to a special class of Cellular Automata and give a hint how our Neural Network Algorithm can be converted to become a Cellular Automaton Algorithm. Cellular automata are simpler than neural networks and well suited for parallel implementation.
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