A Study of the Characteristics of White Noise

A Study of the Characteristics of White Noise

ID:40385804

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时间:2019-08-01

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1、AStudyoftheCharacteristicsofWhiteNoiseUsingtheEmpiricalModeDecompositionMethod12ZhaohuaWuandNordenE.Huang1CenterforOcean-Land-AtmosphereStudies4041PowderMillRd.,Suite302Calverton,MD207052NASAGoddardSpaceFlightCenterCode971Greenbelt,MD20771E-mail:zhwu

2、@cola.iges.orgJanuary2003AbstractBasedonnumericalexperimentsonuniformlydistributedwhitenoiseusingtheEmpiricalModeDecomposition(EMD)method,wefindthattheEMDiseffectivelyadyadicfilter;thattheIntrinsicModeFunction(IMF)componentsareallnormallydistributed,

3、andthattheFourierspectraoftheIMFcomponentsareallidenticalandcoverthesameareaonsemi-logarithmperiodscale.WefurtherdeducethattheproductoftheenergydensityofIMFanditscorrespondingmeanperiodisaconstant,andthattheenergydensityfunctionisChi-squareddistribut

4、ed.WederivetheenergydensityspreadfunctionoftheIMFcomponents.Throughtheseresults,weestablishamethodtoassignstatisticalsignificanceofinformationcontentforIMFcomponentsfromanynoisydata.SouthernOscillationIndexdataareusedtoillustratethemethodologydevelop

5、edhere.1.IntroductionNoiseisaninevitablepartofourexistence.Inscientificstudy,noiseariesinmanyways:Itcouldbepartofthenaturalprocessesgeneratedbylocalandintermittentinstabilitiesandsub-gridphenomena;itcouldbepartoftheconcurrentphenomenaintheenvironment

6、wheretheinvestigationswereconducted;anditcouldalsobepartofthesensorsandrecordingsystems.Asaresult,whenwefacedata,dataisalwaysanamalgamationofsignalandnoise,x(t)=s(t)+n(t),(1)inwhichx(t)isourdata,ands(t)andn(t)areourtruesignalandnoiserespectively.Once

7、thenoisecontaminatesthedata,itisnotatrivialtasktoremoveit.Fortheobviouscases,whentheprocessesarelinearandthenoisehasadistincttimeorfrequencyscalesfromthoseofthetruesignal,Fourierfilterscanbeemployedtoseparatethenoisefromthesignal.But,filtermethodswil

8、lfailwhentheprocessesarenonlinear.Then,evenifthesignalandthenoisehavedistinctfundamentalfrequencies,theharmonicsofthesignalfundamentalcanstillmixwiththenoise.ThismixingofharmonicswithnoisewillrendertheFourierfilterineffectiveasanoiseseparatingmethod.

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