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.
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Copy
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
Copy
@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},}
Copy
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 -