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 une nouvelle mémoire associative nommée Multi-Winner Associative Memory (MWAM) et étudions ses propriétés d'association bidirectionnelle dans cet article. Le MWAM proposé comporte deux processus pour le stockage des paires de modèles : le processus de stockage et le processus de rappel. Pour le processus de stockage, le MWAM proposé peut représenter la moitié d'une paire de modèles dans la couche de représentation distribuée et peut stocker la correspondance du modèle et de sa représentation en utilisant les pondérations ascendantes. De plus, le MWAM peut stocker la correspondance de la représentation distribuée et de l'autre moitié de la paire de modèles dans les pondérations descendantes. Pour le processus de rappel, le MWAM peut rappeler des informations de manière bidirectionnelle : une moitié de la paire de modèles stockée peut être rappelée en recevant l'autre moitié dans la couche d'entrée-sortie pour toutes les paires de modèles stockées.
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Jiongtao HUANG, Masafumi HAGIWARA, "A Multi-Winner Associative Memory" in IEICE TRANSACTIONS on Information,
vol. E82-D, no. 7, pp. 1117-1125, July 1999, doi: .
Abstract: We propose a new associative memory named Multi-Winner Associative Memory (MWAM) and study its bidirectional association properties in this paper. The proposed MWAM has two processes for pattern pairs storage: storage process and recall process. For the storage process, the proposed MWAM can represent a half of pattern pair in the distributed representation layer and can store the correspondence of pattern and its representation using the upward weights. In addition, the MWAM can store the correspondence of the distributed representation and the other half of pattern pair in the downward weights. For the recall process, the MWAM can recall information bidirectionally: a half of the stored pattern pair can be recalled by receiving the other half in the input-output layer for any stored pattern pairs.
URL: https://global.ieice.org/en_transactions/information/10.1587/e82-d_7_1117/_p
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@ARTICLE{e82-d_7_1117,
author={Jiongtao HUANG, Masafumi HAGIWARA, },
journal={IEICE TRANSACTIONS on Information},
title={A Multi-Winner Associative Memory},
year={1999},
volume={E82-D},
number={7},
pages={1117-1125},
abstract={We propose a new associative memory named Multi-Winner Associative Memory (MWAM) and study its bidirectional association properties in this paper. The proposed MWAM has two processes for pattern pairs storage: storage process and recall process. For the storage process, the proposed MWAM can represent a half of pattern pair in the distributed representation layer and can store the correspondence of pattern and its representation using the upward weights. In addition, the MWAM can store the correspondence of the distributed representation and the other half of pattern pair in the downward weights. For the recall process, the MWAM can recall information bidirectionally: a half of the stored pattern pair can be recalled by receiving the other half in the input-output layer for any stored pattern pairs.},
keywords={},
doi={},
ISSN={},
month={July},}
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TY - JOUR
TI - A Multi-Winner Associative Memory
T2 - IEICE TRANSACTIONS on Information
SP - 1117
EP - 1125
AU - Jiongtao HUANG
AU - Masafumi HAGIWARA
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 new associative memory named Multi-Winner Associative Memory (MWAM) and study its bidirectional association properties in this paper. The proposed MWAM has two processes for pattern pairs storage: storage process and recall process. For the storage process, the proposed MWAM can represent a half of pattern pair in the distributed representation layer and can store the correspondence of pattern and its representation using the upward weights. In addition, the MWAM can store the correspondence of the distributed representation and the other half of pattern pair in the downward weights. For the recall process, the MWAM can recall information bidirectionally: a half of the stored pattern pair can be recalled by receiving the other half in the input-output layer for any stored pattern pairs.
ER -