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Elimination of multiple arrows and self-connections in coupled cell networks
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Stewart, Ian, 1945-. (2007) Elimination of multiple arrows and self-connections in coupled cell networks. INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS, 17 (1). pp. 99-106. ISSN 0218-1274
Full text not available from this repository.Abstract
A coupled cell network is a finite directed graph in which nodes and edges are classified into equivalence classes. Such networks arise in a formal theory of coupled systems of differential equations, as a schematic indication of the topology of the coupling, but they can be studied independently as combinatorial objects. The edges of a coupled cell network are "identical" if they are all equivalent, and the network is "homogeneous" if all nodes have isomorphic sets of input edges. Golubitsky et al. [ 2005] proved that every homogeneous identical-edge coupled cell network is a quotient of a network that has no multiple edges and no self-connections. We generalize this theorem to any coupled cell network by removing the conditions of homogeneity and identical edges. The problem is a purely combinatorial assertion about labeled directed graphs, and we give two combinatorial proofs. Both proofs eliminate self-connections inductively. The first proof also eliminates multiple edges inductively, the main feature being the specification of the inductive step in terms of a complexity measure. The second proof obtains a more efficient result by eliminating all multiple edges in a single construction.
| Item Type: | Journal Article |
|---|---|
| Subjects: | Q Science > QA Mathematics Q Science |
| Journal or Publication Title: | INTERNATIONAL JOURNAL OF BIFURCATION AND CHAOS |
| Publisher: | WORLD SCIENTIFIC PUBL CO PTE LTD |
| ISSN: | 0218-1274 |
| Date: | January 2007 |
| Volume: | 17 |
| Number: | 1 |
| Number of Pages: | 8 |
| Page Range: | pp. 99-106 |
| Identification Number: | 10.1142/S0218127407017197 |
| Publication Status: | Published |
| URI: | http://wrap.warwick.ac.uk/id/eprint/31164 |
Data sourced from Thomson Reuters' Web of Knowledge
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