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dc.contributor.author Huelse, Martin
dc.date.accessioned 2008-11-12T18:43:00Z
dc.date.available 2008-11-12T18:43:00Z
dc.date.issued 2008-11-12
dc.identifier.citation Huelse , M 2008 , From Sierpinski carpets to directed graphs . Unknown Publisher . en
dc.identifier.other PURE: 94728
dc.identifier.other dspace: 2160/1095
dc.identifier.uri http://hdl.handle.net/2160/1095
dc.description.abstract We introduce a simple method for a deterministic generation of directed and connected graphs. The method is inspired by Sierpinski carpets forming fractal sets. Despite the large size these graphs can have, the distance between most of the nodes is short, i.e. it scales with log. We will further show that important network properties, such as degree distribution, can directly be determined by the initial structure of this process. These findings lead us to the formulation of general conditions providing a targeted generation of complex networks for initial structures of arbitrary dimension. Under which circumstances these graphs can show scale-free and small-world properties is discussed as well. As a possible application of this method we will finally discuss the generation of artificial neural networks. en
dc.language.iso eng
dc.publisher Unknown Publisher
dc.title From Sierpinski carpets to directed graphs en
dc.type Text en
dc.type.publicationtype Report (commissioned) en
dc.contributor.institution Department of Computer Science en


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