A Simple Learning Algorithm for Network Formation Based on Growing Self-Organizing Maps
Summary :
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.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E87-A No.10 pp.2807-2810
- Publication Date
- 2004/10/01
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- LETTER
- Category
- Nonlinear Problems
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Keyword
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Hiroki SASAMURA, Toshimichi SAITO, Ryuji OHTA, "A Simple Learning Algorithm for Network Formation Based on Growing Self-Organizing Maps" in IEICE TRANSACTIONS on Fundamentals,
vol. E87-A, no. 10, pp. 2807-2810, October 2004, doi: .
Abstract: 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.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e87-a_10_2807/_p
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@ARTICLE{e87-a_10_2807,
author={Hiroki SASAMURA, Toshimichi SAITO, Ryuji OHTA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Simple Learning Algorithm for Network Formation Based on Growing Self-Organizing Maps},
year={2004},
volume={E87-A},
number={10},
pages={2807-2810},
abstract={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.},
keywords={},
doi={},
ISSN={},
month={October},}
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TY - JOUR
TI - A Simple Learning Algorithm for Network Formation Based on Growing Self-Organizing Maps
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2807
EP - 2810
AU - Hiroki SASAMURA
AU - Toshimichi SAITO
AU - Ryuji OHTA
PY - 2004
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E87-A
IS - 10
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - October 2004
AB - 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.
ER -
English
