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System modeling based on machine learning for anomaly detection and predictive maintenance in industrial plants

contributor authorKroll, Bjorn
contributor authorSchaffranek, David
contributor authorSchriegel, Sebastian
contributor authorNiggemann, Oliver
date accessioned2020-03-12T22:21:52Z
date available2020-03-12T22:21:52Z
date issued2014
identifier other7005202.pdf
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/1080460?locale-attribute=fa&show=full
formatgeneral
languageEnglish
publisherIEEE
titleSystem modeling based on machine learning for anomaly detection and predictive maintenance in industrial plants
typeConference Paper
contenttypeMetadata Only
identifier padid8216850
subject keywordsamplify and forward communication
subject keywordsn cooperative communication
subject keywordsn equalisers
subject keywordsn error statistics
subject keywordsn radio spectrum management
subject keywordsn radiofrequency interference
subject keywordsn relay networks (telecommunication)
subject keywordsn BER
subject keywordsn DDST scheme
subject keywordsn PU
subject keywordsn SU
subject keywordsn amplify-and-forward cooperative single carrier-frequency domain equalizer system
subject keywordsn cooperative SC-FDE relaying
subject keywordsn cooperative orthogonal frequency division multiplexing system
subject keywordsn data-dependent superimposed training scheme
subject keywordsn primary use
identifier doi10.1109/ICC.2014.6884007
journal titlemerging Technology and Factory Automation (ETFA), 2014 IEEE
filesize3501404
citations0


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