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Towards more accurate multi-label software behavior learning

date accessioned2020-03-12T19:31:15Z
date available2020-03-12T19:31:15Z
date issued2014
identifier other6747163.pdf
identifier urihttp://libsearch.um.ac.ir:80/fum/handle/fum/980460?show=full
formatgeneral
languageEnglish
publisherIEEE
titleTowards more accurate multi-label software behavior learning
typeConference Paper
contenttypeMetadata Only
identifier padid8094786
subject keywordsCMOS integrated circuits
subject keywordsSRAM chips
subject keywordsVLSI
subject keywordslow-power electronics
subject keywordsVLSI design
subject keywordsadiabatic SRAM
subject keywordsdigital chip
subject keywordsfrequency 10 MHz to 200 MHz
subject keywordslow power memory cell structures
subject keywordsmemory circuits
subject keywordspower reduction
subject keywordsstatic CMOS implementation
subject keywordstechnology scaling
subject keywordsCMOS integrated circuits
subject keywordsCircuit stability
subject keywordsMicroprocessors
subject keywordsPower demand
subject keywordsSRAM cells
subject keywordsTransistors
subject keywordsEnergy Recovery
subject keywordsIRS scheme
subject keywordsMemory
subject keywordsStack effect
identifier doi10.1109/ICGCCEE.2014.6922280
journal titleoftware Maintenance, Reengineering and Reverse Engineering (CSMR-WCRE), 2014 Software Evolution Week
filesize403014
citations0
contributor rawauthorXin Xia , Yang Feng , Lo, D. , Zhenyu Chen , Xinyu Wang


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