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Conference Paper: Supervised learning of the adaptive resonance theory system
Title | Supervised learning of the adaptive resonance theory system |
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Authors | |
Issue Date | 1994 |
Publisher | IEEE. |
Citation | Proceedings of the 1994 International Symposium on Artificial Neural Networks (ISANN '94), National Cheng Kung University, Tainan, Taiwan, 15-17 December 1994, p. 63-68 How to Cite? |
Abstract | A supervised learning ART model (SART) is proposed which is based on the structure of ARTMAP but is much simpler. The techniques of match tracking and complement coding have been implemented to ensure the correct selection of category and stability during the training and testing phases. Two simulations have been done in order to verify and evaluate the classification power of SART. The result of identification of poisonous mushroom by SART is compared with that by ARTMAP. |
Persistent Identifier | http://hdl.handle.net/10722/53616 |
DC Field | Value | Language |
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dc.contributor.author | So, YT | en_HK |
dc.contributor.author | Chan, KP | en_HK |
dc.date.accessioned | 2009-04-03T07:24:44Z | - |
dc.date.available | 2009-04-03T07:24:44Z | - |
dc.date.issued | 1994 | en_HK |
dc.identifier.citation | Proceedings of the 1994 International Symposium on Artificial Neural Networks (ISANN '94), National Cheng Kung University, Tainan, Taiwan, 15-17 December 1994, p. 63-68 | en_HK |
dc.identifier.uri | http://hdl.handle.net/10722/53616 | - |
dc.description.abstract | A supervised learning ART model (SART) is proposed which is based on the structure of ARTMAP but is much simpler. The techniques of match tracking and complement coding have been implemented to ensure the correct selection of category and stability during the training and testing phases. Two simulations have been done in order to verify and evaluate the classification power of SART. The result of identification of poisonous mushroom by SART is compared with that by ARTMAP. | en_HK |
dc.language | eng | en_HK |
dc.publisher | IEEE. | en_HK |
dc.relation.ispartof | Proceedings of the 1994 International Symposium on Artificial Neural Networks (ISANN '94) | - |
dc.rights | ©1994 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. | en_HK |
dc.title | Supervised learning of the adaptive resonance theory system | en_HK |
dc.type | Conference_Paper | en_HK |
dc.identifier.email | Chan, KP: kpchan@cs.hku.hk | en_HK |
dc.description.nature | published_or_final_version | en_HK |
dc.identifier.hkuros | 5538 | - |