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Dong, LI, LIU, Shulin, ZHANG, Hongli (2017) A method of anomaly detection and fault diagnosis with online adaptive learning under small training samples. Pattern Recognition, 64. 374-385 doi:10.1016/j.patcog.2016.11.026

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Reference TypeJournal (article/letter/editorial)
TitleA method of anomaly detection and fault diagnosis with online adaptive learning under small training samples
JournalPattern Recognition
AuthorsDong, LIAuthor
LIU, ShulinAuthor
ZHANG, HongliAuthor
Year2017 (April)Volume64
PublisherElsevier BV
DOIdoi:10.1016/j.patcog.2016.11.026Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID9366858Long-form Identifiermindat:1:5:9366858:1
GUID0
Full ReferenceDong, LI, LIU, Shulin, ZHANG, Hongli (2017) A method of anomaly detection and fault diagnosis with online adaptive learning under small training samples. Pattern Recognition, 64. 374-385 doi:10.1016/j.patcog.2016.11.026
Plain TextDong, LI, LIU, Shulin, ZHANG, Hongli (2017) A method of anomaly detection and fault diagnosis with online adaptive learning under small training samples. Pattern Recognition, 64. 374-385 doi:10.1016/j.patcog.2016.11.026
In(2017) Pattern Recognition Vol. 64. Elsevier BV

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