模糊竞争学习矢量量化 FCLVQ
提出了一种新的基于模糊竞争学习的自调整的模糊建模方法。
The author proposes a new self tuning fuzzy modeling by means of fuzzy competitive learning.
针对新的参考向量开发了模糊竞争学习模式，并用该算法成功地解决了文献聚类的难题。
This paper also develops a fuzzy competitive learning scheme for these new reference vector parameters, and applies the algorithm to the difficult task of clustering documents.
先通过基于模糊竞争学习确定一种在线模糊辨识算法，并给出递推模糊竞争学习算法收敛性证明。
First of all, an on-line fuzzy identifying algorithm is confirmed by means of fuzzy competitive learning, and the convergence about a recursive algorithm of fuzzy competitive learning is proved.
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