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Error-adaptive classifier boosting (EACB): Exploiting data-driven training for highly fault-tolerant hardware

contributor authorZhuo Wang , Schapire, R. , Verma, N.
date accessioned2020-03-12T20:09:21Z
date available2020-03-12T20:09:21Z
date issued2014
identifier other6854329.pdf
identifier urihttps://libsearch.um.ac.ir:443/fum/handle/fum/1003955?show=full
formatgeneral
languageEnglish
publisherIEEE
titleError-adaptive classifier boosting (EACB): Exploiting data-driven training for highly fault-tolerant hardware
typeConference Paper
contenttypeMetadata Only
identifier padid8125247
subject keywordsSPICE
subject keywordsequivalent circuits
subject keywordsfrequency selective surfaces
subject keywordsrational functions
subject keywordsADS SPICE generator
subject keywordsCST Microwave Studio
subject keywordscircular ring FSS
subject keywordscross ring FSS
subject keywordsequivalent circuit model
subject keywordsfrequency analyses
subject keywordsfrequency selective surfaces
subject keywordsmicrostructure simulation
subject keywordsrational function approximation approach
subject keywordssimulation program with integrated circuit emphasis
subject keywordstime analyses
subject keywordsvector fitting
subject keywordsEquivalent circuits
subject keywordsFrequency selective surfaces
subject keywordsIntegrated circuit modeling
subject keywordsMicrowave circuits
subject keywordsRLC circuits
subject keywordsR
identifier doi10.1109/APCAP.2014.6992686
journal titlecoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
filesize235119
citations0


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