Classification of Networks Using Network Functions

Authors:
Makoto Uchida;Susumu Shirayama
Affiliations:
School of Engineering, the University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8568, Japan;Research into Artifacts, Center for Engineering, the University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8568, Japan
Venue:
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part II
Year:
2007

Citing 3
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Abstract

We propose a new classification of complex networks in association with a functionof networks. Networks are considered to be input-output system where the initial condition is input and the evolving dynamics is output. We study a functional relationship between the input and the output which depend on network structures. A function of network are modeled as a spin interaction system driven by Glauber dynamics with arbitrary initial conditions. Through numerical studies, we show a novel classification of networks. The results are applied to examples of real-world networks, which proved the classification to be useful for analysis of the inherent characteristics and model assumption for the real-world networks.