Titlebook: Cellular Automata; 6th International Co Peter M. A. Sloot,Bastien Chopard,Alfons G. Hoekst Conference proceedings 2004 Springer-Verlag Berl

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,Ein Kapitel für sich: die Lehrenden,d between the cell’s update-rules in a local manner, allowing for easy parallelization. As a case study, the algorithm was applied to the density classification problem: classifying any given initial configuration according to the percentage of 1-valued cells. The main result presented in this paper

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Tom Thumb Algorithm and von Neumann Universal Constructor,f multi-processor systems. Except for the cell construction process, every functionality of the original CA has been preserved in our new system. Moreover, the Tom Thumb Algorithm now allows the replication of any structure within the von Neumann environment, whatever its number of cells may be.

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Computing Phase Shifts of Maximum-Length 90/150 Cellular Automata Sequences,ting the relative phase shifts of all pseudo-noise sequences which have the same characteristic polynomial. As a special case of this method, we give an algorithm to compute relative phase shifts between stages of a CA. This is a very simple and efficient method than the already proposed methods.

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Cellular Automata Evolution for Distributed Data Mining,ting model of a special class of sparse network referred to as Cellular Automata (CA). Extensive experimental results confirm scalability of the PCM to handle distributed datasets. The excellent classification accuracy and low memory overhead figure establish the proposed PCM as the classifier ideally suited for DDM environments.

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Randomized Computation with Cellular Automata, runs over the same problem instance to improve the quality of the answer. We consider the case of the so-called density task and quantify the interest of the approach. In addition we show that almost 100% of success can be achieved provided that the density task is allowed to classify the configuration in three rather than two classes.

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Peter M. A. Sloot,Bastien Chopard,Alfons G. HoekstIncludes supplementary material:

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