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28 March 2024
 
  » arxiv » nlin.AO/0111023

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Evolutionary reconstruction of networks
Mads Ipsen ; Alexander S. Mikhailov ;
Date 9 Nov 2001
Subject Adaptation and Self-Organizing Systems; Disordered Systems and Neural Networks; Soft Condensed Matter | nlin.AO cond-mat.dis-nn cond-mat.soft
AbstractCan a graph specifying the pattern of connections of a dynamical network be reconstructed from statistical properties of a signal generated by such a system? In this model study, we present an evolutionary algorithm for reconstruction of graphs from their Laplacian spectra. Through a stochastic process of mutations and selection, evolving test networks converge to a reference graph. Applying the method to several examples of random graphs, clustered graphs, and small-world networks, we show that the proposed stochastic evolution allows exact reconstruction of relatively small networks and yields good approximations in the case of large sizes.
Source arXiv, nlin.AO/0111023
Other source [GID 232117] pmid12443261
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