简介:<正>日前,德州仪器(TI)宣布推出一款SimpleLinkSub-1GHzCC1200收发器,进一步壮大其高性能RF产品线阵营。该CC1200具有业界领先的覆盖范围与共存性,以及高达1Mbps的数据速率,专门针对高级电表基础设施(AMI)及家域网(HAN)的1GHz以下无线连接而开发,可充分满足智能电网、家庭楼宇自动化以及告警与安全系统应用需求。CC1200支持嗅探模式与快速建立时间,可通过低功耗工作提供长达数年的电池使用寿命。CC1200是一款高度灵活的RF解决方案,支持原有1GHz以下系统、所有具有硬件数据包处理与硬件AES安全支持的IEEE802.15.4gFSK模式,以及所有无线M-Bus(wM-Bus)模式。
简介:AnapproximationalgorithmispresentedforaugmentinganundirectedweightedgraphtoaK-edge-connectedgraph.Thealgorithmisusefulfordesigningareliablenetwork.
简介:InviewofK-faulttestability,thetopologicalconstructionofapracticalcircuitisfarfromideal.Inordertoimprovethetestabilityofacircuit,wemayincreasethenumberofaccessiblenodesorusethemulti-excitationmethod.Effectivenessofthesemethodsandthefeasibilityofchoosingaccessiblenodesarediscussedindetail.Theconditionsformulti-excitationtestabilityarepresented.
简介:Blindrecognitionofconvolutionalcodesisnotonlyessentialforcognitiveradio,butalsofornon-cooperativecontext.Thispaperisdedicatedtotheblindidentificationofratek/nconvolutionalencodersinanoisycontextbasedonWalsh-Hadamardtransformationandblockmatrix(WHT-BM).Theproposedalgorithmconstructsasystemofnoisylinearequationsandutilizesallitscoefficientstorecoverparitycheckmatrix.Itisabletomakeuseoffault-tolerantfeatureofWHT,thusprovidingmoreaccurateresultsandachievingbettererrorperformanceinhighrawbiterrorrate(BER)regions.Moreover,itismorecomputationallyefficientwiththeuseoftheblockmatrix(BM)method.
简介:Higher-orderalmostcyclostationarycomplexprocessesarecomplexrandomsignalswithalmostperiodicallytime-varyingstatistics,whichisimportanttotheresearchofnon-Gaussiansignalsininformationsystem.Intinspaper,smoothedpolyperiodogramsareproposedforrelatedtocyclicpolyspectralestimationandareshowntobeconsistentandasymptoticallycomplexnormal.Asymptoticcovarianceexpressionsarederivedalongwiththeircomputableforms.
简介:Comparedwithaccuratediagnosis,thesystem’sselfdiagnosingcapabilitycanbegreatlyincreasedthroughthet/kdiagnosisstrategyatmostkvertexestobemistakenlyidentifiedasfaultyunderthecomparisonmodel,wherekistypicallyasmallnumber.BasedonthePreparata,Metze,andChien(PMC)model,then-dimensionalhypercubenetworkisprovedtobet/kdiagnosable.Inthispaper,basedontheMaengandMalek(MM)?model,anovelt/k-faultdiagnosis(1k4)algorithmofndimensionalhypercube,calledt/k-MM?-DIAG,isproposedtoisolateallfaultyprocessorswithinthesetofnodes,amongwhichthenumberoffault-freenodesidentifiedwronglyasfaultyisatmostk.ThetimecomplexityinouralgorithmisonlyO(2nn2).
简介:Graphicprocessingunits(GPUs)havebeenwidelyrecognizedascost-efficientco-processorswithacceptablesize,weight,andpowerconsumption.However,adoptingGPUsinreal-timesystemsisstillchallenging,duetothelackinframeworkforreal-timeanalysis.Inordertoguaranteereal-timerequirementswhilemaintainingsystemutilizationinmodernheterogeneoussystems,suchasmulticoremulti-GPUsystems,anovelsuspension-basedk-exclusionreal-timelockingprotocolandtheassociatedsuspension-awareschedulabilityanalysisareproposed.TheproposedprotocolprovidesasynchronizationframeworkthatenablesmultipleGPUstobeefficientlyintegratedinmulticorereal-timesystems.Comparativeevaluationsshowthattheproposedmethodsimproveupontheexistingworkintermsofschedulability.