Nonlinear Sciences – Adaptation and Self-Organizing Systems
Scientific paper
2001-11-09
Nonlinear Sciences
Adaptation and Self-Organizing Systems
4 pages, 4 figures. Please, address all correspondence to ipsen@fhi-berlin.mpg.de
Scientific paper
10.1103/PhysRevE.66.046109
Can 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.
Ipsen Mads
Mikhailov Alexander S.
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