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(2006)

Cluster detection algorithm in neural networks

David Meunier 1, Hélène Paugam-Moisy 1

(2006)

Complex networks have received much attention in the last few years, and reveal global properties of interacting systems in domains like biology, social sciences and technology. One of the key feature of complex networks is their clusterized structure. Most methods applied to study complex networks are based on undirected graphs. However, when considering neural networks, the directionality of links is fundamental. In this article, a method of cluster detection is extended for directed graphs. We show how the extended method is more efficient to detect a clusterized structure in neural networks, without significant increase of the computational cost.

1 :	Institut des Sciences Cognitives (ISC)
	CNRS : UMR5015 – Université Claude Bernard - Lyon I

Domaine

:

Sciences cognitives/Informatique

Mots Clés : Complex networks – cluster detection – directed graph – neural networks

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Contributeur : David Meunier <>

Soumis le : Mardi 16 Mai 2006, 19:20:57

Dernière modification le : Mardi 16 Mai 2006, 20:36:46