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1、英文原文CombinedAdaptiveFilterwithLMS-BasedAlgorithmsBoˇzoKrstaji´c,LJubiˇsaStankovi´c,andZdravkoUskokovi´Abstract:Acombinedadaptivefilterisproposed.ItconsistsofparallelLMS-basedadaptiveFIRfiltersandanalgorithmforchoosingthebetteramongthem.Asacriterionforcomparisonoftheconsideredalgor
2、ithmsintheproposedfilter,wetaketheratiobetweenbiasandvarianceoftheweightingcoefficients.Simulationsresultsconfirmtheadvantagesoftheproposedadaptivefilter.Keywords:Adaptivefilter,LMSalgorithm,Combinedalgorithm,Biasandvariancetrade-off1．IntroductionAdaptivefiltershavebeenappliedinsignal
3、processingandcontrol,aswellasinmanypracticalproblems,[1,2].Performanceofanadaptivefilterdependsmainlyonthealgorithmusedforupdatingthefilterweightingcoefficients.ThemostcommonlyusedadaptivesystemsarethosebasedontheLeastMeanSquare(LMS)adaptivealgorithmanditsmodifications(LMS-basedalgo
4、rithms).TheLMSissimpleforimplementationandrobustinanumberofapplications[1–3].However,sinceitdoesnotalwaysconvergeinanacceptablemanner,therehavebeenmanyattemptstoimproveitsperformancebytheappropriatemodifications:signalgorithm(SA)[8],geometricmeanLMS(GLMS)[5],variablestep-sizeLMS(
5、VSLMS)[6,7].EachoftheLMS-basedalgorithmshasatleastoneparameterthatshouldbedefinedpriortotheadaptationprocedure(stepforLMSandSA;stepandsmoothingcoefficientsforGLMS;variousparametersaffectingthestepforVSLMS).Theseparameterscruciallyinfluencethefilteroutputduringtwoadaptationphases:tra
6、nsientandsteadystate.Choiceoftheseparametersismostlybasedonsomekindoftrade-offbetweenthequalityofalgorithmperformanceinthementionedadaptationphases.WeproposeapossibleapproachfortheLMS-basedadaptivefilterperformanceimprovement.Namely,wemakeacombinationofseveralLMS-basedFIRfilterswi
7、thdifferentparameters,andprovidethecriterionforchoosingthemostsuitablealgorithmfordifferentadaptationphases.ThismethodmaybeappliedtoalltheLMS-basedalgorithms,althoughwehereconsideronlyseveralofthem.Thepaperisorganizedasfollows.AnoverviewoftheconsideredLMS-basedalgorithmsisgiveni
8、nSection2.Section3proposesthecriterionforevalua
