The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Nous proposons un algorithme d'apprentissage pour les réseaux de neurones auto-organisés afin de former une carte préservant la topologie à partir d'un collecteur d'entrée dont la topologie peut changer dynamiquement. Les résultats expérimentaux montrent que le réseau utilisant l'algorithme proposé peut rapidement s'ajuster pour représenter la topologie des distributions d'entrée non stationnaires.
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Taira NAKAJIMA, Hiroyuki TAKIZAWA, Hiroaki KOBAYASHI, Tadao NAKAMURA, "A Topology Preserving Neural Network for Nonstationary Distributions" in IEICE TRANSACTIONS on Information,
vol. E82-D, no. 7, pp. 1131-1135, July 1999, doi: .
Abstract: We propose a learning algorithm for self-organizing neural networks to form a topology preserving map from an input manifold whose topology may dynamically change. Experimental results show that the network using the proposed algorithm can rapidly adjust itself to represent the topology of nonstationary input distributions.
URL: https://global.ieice.org/en_transactions/information/10.1587/e82-d_7_1131/_p
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@ARTICLE{e82-d_7_1131,
author={Taira NAKAJIMA, Hiroyuki TAKIZAWA, Hiroaki KOBAYASHI, Tadao NAKAMURA, },
journal={IEICE TRANSACTIONS on Information},
title={A Topology Preserving Neural Network for Nonstationary Distributions},
year={1999},
volume={E82-D},
number={7},
pages={1131-1135},
abstract={We propose a learning algorithm for self-organizing neural networks to form a topology preserving map from an input manifold whose topology may dynamically change. Experimental results show that the network using the proposed algorithm can rapidly adjust itself to represent the topology of nonstationary input distributions.},
keywords={},
doi={},
ISSN={},
month={July},}
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TY - JOUR
TI - A Topology Preserving Neural Network for Nonstationary Distributions
T2 - IEICE TRANSACTIONS on Information
SP - 1131
EP - 1135
AU - Taira NAKAJIMA
AU - Hiroyuki TAKIZAWA
AU - Hiroaki KOBAYASHI
AU - Tadao NAKAMURA
PY - 1999
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E82-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 1999
AB - We propose a learning algorithm for self-organizing neural networks to form a topology preserving map from an input manifold whose topology may dynamically change. Experimental results show that the network using the proposed algorithm can rapidly adjust itself to represent the topology of nonstationary input distributions.
ER -