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	A method of anomaly detection and fault diagnosis with online adaptive learning under small training samples
	Li, Dong[1]; Liu, Shulin[2]; Zhang, Hongli[3]
刊名	PATTERN RECOGNITION
	2017
卷号	64页码:374-385
关键词	Artificial immune system Anomaly detection Fault diagnosis Classification Clustering
ISSN号	0031-3203
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/2193768
专题	上海大学
作者单位	1.[1]Shanghai Univ, Sch Mechatron Engn & Automat, Shanghai 200072, Peoples R China. 2.Changzhou Univ, Sch Petr Engn, Changzhou 213164, Peoples R China. 3.[2]Shanghai Univ, Sch Mechatron Engn & Automat, Shanghai 200072, Peoples R China. 4.[3]Shanghai Univ, Sch Mechatron Engn & Automat, Shanghai 200072, Peoples R China.
推荐引用方式 GB/T 7714	Li, Dong[1],Liu, Shulin[2],Zhang, Hongli[3]. A method of anomaly detection and fault diagnosis with online adaptive learning under small training samples[J]. PATTERN RECOGNITION,2017,64:374-385.
APA	Li, Dong[1],Liu, Shulin[2],&Zhang, Hongli[3].(2017).A method of anomaly detection and fault diagnosis with online adaptive learning under small training samples.PATTERN RECOGNITION,64,374-385.
MLA	Li, Dong[1],et al."A method of anomaly detection and fault diagnosis with online adaptive learning under small training samples".PATTERN RECOGNITION 64(2017):374-385.

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