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Style-based abstractions for human motion classification

contributor authorLaViers, A. , Egerstedt, M.
date accessioned2020-03-12T19:58:33Z
date available2020-03-12T19:58:33Z
date issued2014
identifier other6843713.pdf
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/997219?locale-attribute=fa&show=full
formatgeneral
languageEnglish
publisherIEEE
titleStyle-based abstractions for human motion classification
typeConference Paper
contenttypeMetadata Only
identifier padid8117128
subject keywordsfeedback
subject keywordsfunction approximation
subject keywordslinear systems
subject keywordsneurocontrollers
subject keywordsconstrained linear system
subject keywordsfunction approximation
subject keywordsinput-output manifold
subject keywordsneural network fitting
subject keywordsnoise measurement
subject keywordsonline control law
subject keywordsset invariance
subject keywordsComputational modeling
subject keywordsManifolds
subject keywordsNeural networks
subject keywordsNoise
subject keywordsOutput feedback
subject keywordsRuntime
identifier doi10.1109/CICA.2014.7013246
journal titleyber-Physical Systems (ICCPS), 2014 ACM/IEEE International Conference on
filesize985219
citations0


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