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基于EMDCLEAN的图像去噪方法

来源:用户上传      作者:曾展挺

  
  摘要:魍车闹斩松璞附诘闶侗鸱椒ㄎ醇扑憬诘悴舛戎副辏导致其节点识别效率和识别率低、识别速度慢。为此,基于边缘计算技术设计了新的终端设备远程部署节点智能识别方法。首先采用希尔伯特变换技术,将处于时域的终端设备信号分解为复频域信号的频率和相位,并确定节点关联程度,建立终端设备网络空间模型;然后利用边缘计算技术设计节点参考框架,计算节点子图和最大邻居连通密度测度,从而实现对终端设备远程部署节点的有效识别。实验结果表明:本方法识别终端设备远程部署节点所需的时间更短,且对节点的变化更为敏感,具有较高的识别效率和节点识别率。
  关键词:边缘计算技术;终端设备;远程部署节点;节点识别;节点关联程度;连通密度
  中图分类号:TP399文献标识码:A
  
  ResearchonIntelligentIdentificationofRemote
  DeploymentNodeofYerminalEquipmentBased
  onEdgeComputingTechnology
  
  LUYuhua,GAOWenjun,ZHANGWei
  (BeijingZhixinSemiconductorTechnologyCo.,Ltd.,Beijing102200,China)
  Abstract:Thetraditionalnoderecognitionmethodofterminalequipmentdoesnotcalculatethenodemeasureindex,whichleadstothelownoderecognitionefficiencyandrecognitionrateandslowrecognitionspeed.Forthisreason,anewintelligentidentificationmethodforremotedeploymentnodesofterminalequipmentisdesignedbasedonedgecomputingtechnology.Firstly,thesignalinthetimedomainisdecomposedintothefrequencyandphaseofthesignalinthecomplexfrequencydomainbyusingtheHilberttransformtechnology,andthenodecorrelationdegreeisdeterminedtoestablishthenetworkspacemodeloftheterminalequipment.Then,thenodereferenceframeisdesignedbyusingedgecomputingtechnology,andthenodesubplotandthemaximumneighborconnectivitydensitymeasurearecalculated,soastorealizetheeffectiveidentificationoftheterminalequipmentremotedeploymentnode.Theexperimentalresultsshowthattheproposedmethodtakeslesstimetoidentifytheremotedeploymentnodesofterminalequipment,andismoresensitivetothechangesofnodes,andhashigherrecognitionefficiencyandnoderecognitionrate.

nlc202204191400



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