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Odor discrimination using adaptive resonance theory

被引：26
作者：
Distante, C
Siciliano, P
Vasanelli, L
机构：
[1] Univ Lecce, Dipartimento Ingn Innovazione, I-73100 Lecce, Italy
[2] CNR, IME, I-73100 Lecce, Italy
来源：
SENSORS AND ACTUATORS B-CHEMICAL | 2000年 / 69卷 / 03期
关键词：
olfaction; adaptive resonance theory; fuzzy logic; parameter drift;
D O I：
10.1016/S0925-4005(00)00502-5
中图分类号：
O65 [分析化学];
学科分类号：
070302 ; 081704 ;
摘要：
The paper presents two neural networks based on the adaptive resonance theory (ART) for the recognition of several odors subjected to drift. The neural networks developed by Grossberg (supervised and unsupervised) have been used for two different drift behaviors. One in which the clusters end up to overlap each other and the other when they do not. The latter case is solved by unsupervision, which is useful to track the moving clusters and possibly discover new odors autonomously. (C) 2000 Elsevier Science S.A. All rights reserved.
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收藏
页码：248 / 252
页数：5
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