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A fuzzy classifier with adaptive learning of norm inducing matrix

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1 引文 斯高帕斯(Scopus)

摘要

A fuzzy classifier with adaptive learning of the volume of norm inducing matrix is proposed in this paper. The proposed fuzzy classifier improves the Gustafson-Kessel (GK) algorithm which assumes a fixed volume of the norm inducing matrix. An efficient approach based on gradient descent learning is proposed to recursively update the volume of norm inducing matrix. Mathematical analyses and computer simulations are made to show the effectiveness and efficiency of the proposed fuzzy classifier.

原文English
主出版物標題2007 IEEE International Conference on Networking, Sensing and Control, ICNSC'07
頁面362-367
頁數6
DOIs
出版狀態Published - 2007
事件2007 IEEE International Conference on Networking, Sensing and Control, ICNSC'07 - London, United Kingdom
持續時間: 15 4月 200717 4月 2007

出版系列

名字2007 IEEE International Conference on Networking, Sensing and Control, ICNSC'07

Conference

Conference2007 IEEE International Conference on Networking, Sensing and Control, ICNSC'07
國家/地區United Kingdom
城市London
期間15/04/0717/04/07

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