Use of the Fuzzy Self-Organizing Map in pattern recognition

P. Vuorimaa
{"title":"Use of the Fuzzy Self-Organizing Map in pattern recognition","authors":"P. Vuorimaa","doi":"10.1109/FUZZY.1994.343837","DOIUrl":null,"url":null,"abstract":"Kohonen's self-organizing map is one of the best-known neural network models. In previous work, we developed a fuzzy version of the model called: Fuzzy Self-Organizing Map (T. Kohonen, 1988). The new version is similar to the fuzzy logic controllers, and thus it is easy to use and computationally efficient. On the other hand, since the Fuzzy Self-Organizing Map is derived from the original model, the Kohonen learning laws can be used to tune the system. We show how the Fuzzy Self-Organizing Map can be used in pattern recognition. For this purpose, we introduce a new multiple input, multiple output version of the Fuzzy Self-Organizing Map.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"172 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FUZZY.1994.343837","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18

Abstract

Kohonen's self-organizing map is one of the best-known neural network models. In previous work, we developed a fuzzy version of the model called: Fuzzy Self-Organizing Map (T. Kohonen, 1988). The new version is similar to the fuzzy logic controllers, and thus it is easy to use and computationally efficient. On the other hand, since the Fuzzy Self-Organizing Map is derived from the original model, the Kohonen learning laws can be used to tune the system. We show how the Fuzzy Self-Organizing Map can be used in pattern recognition. For this purpose, we introduce a new multiple input, multiple output version of the Fuzzy Self-Organizing Map.<>
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
模糊自组织映射在模式识别中的应用
Kohonen的自组织图是最著名的神经网络模型之一。在之前的工作中,我们开发了一个模型的模糊版本,称为:模糊自组织地图(T. Kohonen, 1988)。新版本与模糊逻辑控制器相似,因此易于使用且计算效率高。另一方面,由于模糊自组织映射来源于原始模型,因此可以使用Kohonen学习定律对系统进行调整。我们展示了模糊自组织映射在模式识别中的应用。为此,我们引入了一种新的多输入、多输出版本的模糊自组织映射。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Fuzzy inputs Tuning method of linguistic membership functions Possibilistic evidential reasoning systems on systolic arrays Fuzzy linearization for nonlinear systems: a preliminary study A fuzzy logic approach to intelligent alarms in cardioanesthesia
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1