| Literature DB >> 15783941 |
Barbara Drossel1, Tamara Mihaljev, Florian Greil.
Abstract
The Kauffman model describes a system of randomly connected nodes with dynamics based on Boolean update functions. Though it is a simple model, it exhibits very complex behavior for "critical" parameter values at the boundary between a frozen and a disordered phase, and is therefore used for studies of real network problems. We prove here that the mean number and mean length of attractors in critical random Boolean networks with connectivity one both increase faster than any power law with network size. We derive these results by generating the networks through a growth process and by calculating lower bounds.Entities:
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Year: 2005 PMID: 15783941 DOI: 10.1103/PhysRevLett.94.088701
Source DB: PubMed Journal: Phys Rev Lett ISSN: 0031-9007 Impact factor: 9.161