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	A modified gradient learning algorithm with smoothing L-1/2 regularization for Takagi-Sugeno fuzzy models
	Liu, Yan; Wu, Wei; Fan, Qinwei; Yang, Dakun; Wang, Jian
刊名	NEUROCOMPUTING
	2014
卷号	138页码:229-237
关键词	Takagi-Sugeno (T-S) fuzzy models Gradient descent method Convergence Gaussian-type membership function Variable selection Regularizer
ISSN号	0925-2312
URL标识	查看原文
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/4427299
专题	大连理工大学
作者单位	1.Dalian Polytech Univ, Sch Informat Sci & Engn, Dalian 116034, Peoples R China. 2.Dalian Univ Technol, Sch Math Sci, Dalian 116024, Peoples R China. 3.China Univ Petr, Sch Math & Computat Sci, Dongying 257061, Peoples R China.
推荐引用方式 GB/T 7714	Liu, Yan,Wu, Wei,Fan, Qinwei,et al. A modified gradient learning algorithm with smoothing L-1/2 regularization for Takagi-Sugeno fuzzy models[J]. NEUROCOMPUTING,2014,138:229-237.
APA	Liu, Yan,Wu, Wei,Fan, Qinwei,Yang, Dakun,&Wang, Jian.(2014).A modified gradient learning algorithm with smoothing L-1/2 regularization for Takagi-Sugeno fuzzy models.NEUROCOMPUTING,138,229-237.
MLA	Liu, Yan,et al."A modified gradient learning algorithm with smoothing L-1/2 regularization for Takagi-Sugeno fuzzy models".NEUROCOMPUTING 138(2014):229-237.

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