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A Simple Learning Algorithm for Network Formation Based on Growing Self-Organizing Maps
Hiroki SASAMURA Toshimichi SAITO Ryuji OHTA
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 2004/10/01
Print ISSN: 0916-8508
Type of Manuscript: LETTER
Category: Nonlinear Problems
unsupervised learning, self-organizing feature maps, growing cell structures, small-world network,
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This paper presents a simple learning algorithm for network formation. The algorithm is based on self-organizing maps with growing cell structures and can adapt input data which correspond to nodes of the network. In basic numerical experiments, as a parameter is selected suitably, our algorithm can generate network having small-world-like structure. Such network structure appears in some natural networks and has advantages in practical systems.