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题名: Method for improving classification performance of neural network based on fuzzy input and network inversion
作者: Wu, Y;  Wang, SJ
发表日期: 2005
摘要: In order to effectively improve the classification performance of neural network, first architecture of fuzzy neural network with fuzzy input was proposed. Next a cost function of fuzzy outputs and non-fuzzy targets was defined. Then a learning algorithm from the cost function for adjusting weights was derived. And then the fuzzy neural network was inversed and fuzzified inversion algorithm was proposed. Finally, computer simulations on real-world pattern classification problems examine the effectives of the proposed approach. The experiment results show that the proposed approach has the merits of high learning efficiency, high classification accuracy and high generalization capability.
刊名: JOURNAL OF INFRARED AND MILLIMETER WAVES
专题: 中国科学院半导体研究所(2009年前)_期刊论文

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推荐引用方式:
Wu, Y; Wang, SJ .Method for improving classification performance of neural network based on fuzzy input and network inversion ,JOURNAL OF INFRARED AND MILLIMETER WAVES,FEB 2005,24 (1):15-18
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