计算机工程与应用 ›› 2008, Vol. 44 ›› Issue (28): 49-50.DOI: 10.3778/j.issn.1002-8331.2008.28.016
• 理论研究 • 上一篇 下一篇
徐玲玲,李朝峰,潘婷婷
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XU Ling-ling,LI Chao-feng,PAN Ting-ting
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摘要： 对模糊ART神经网络模型中的类别选择方法进行改进，并在权值向量的修改规则中引入隶属度，得到一种改进的Fuzzy ART学习算法。IRIS数据分类结果证明了新方法的可行性。
关键词: 模糊自适应共振理论, 隶属度, 模式分类
Abstract: In this paper，we improve the cluster-choose way of Fuzzy ART neural network，and moreover introduce the membership degree into the updating rule of connection weight vector，and then gain an improved Fuzzy ART learning algorithm.IRIS data classification results prove the validity of the new algorithm.
Key words: Fuzzy Adaptive Resonance Theory, membership degree, pattern classification
徐玲玲,李朝峰,潘婷婷. 一种改进的模糊ART神经网络学习算法[J]. 计算机工程与应用, 2008, 44(28): 49-50.
XU Ling-ling,LI Chao-feng,PAN Ting-ting. Improved fuzzy ART neural network learning algorithm[J]. Computer Engineering and Applications, 2008, 44(28): 49-50.
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链接本文: http://cea.ceaj.org/CN/10.3778/j.issn.1002-8331.2008.28.016
http://cea.ceaj.org/CN/Y2008/V44/I28/49
