简介：Basedondiscretewavelettransform,bothrelativewaveletenergy(RWE)andsegmentwaveletentropy(SWE)ofelectroencephalogram(EEG)aredefinedinthispaper.TheRWEprovidesquantitativelytheinformationabouttherelativeenergyassociatedwithdifferentfrequencybandspresentintheEEG.TheSWEcarriesinformationaboutthedegreeoforderordisorderassociatedwithdifferenttimesegmentofEEGevolution,whichcandeterminethetime-segmentlocalizationsofabnormaldynamicprocessesofbrainactivityduetothelocalizationcharacteristicsofthewavelettransform.TheexperimentalresultsshowthattheRWEandSWEaredifferentbetweenepilepticEEGsandnormalEEGs,whichdemonstratethattheRWEandtheSWEarehelpfultoanalyzethedynamicbehaviorofdifferentEEGs.

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简介：Lidarisaneffectivetoolforremotelymonitoringtargetorobject,butthelidarsignalisoftenaffectedbyvariousnoisesorinterferences.Therefore,detectingtheweaksignalsburiedinnoisesisafundamentalandimportantprobleminthelidarsystems.Inthispaper,aneffectivenoisereductionmethodcombiningwaveletimprovedthresholdwithwaveletdomainspatialfiltrationispresentedtodenoisepulselidarsignalandisinvestigatedbydetectingthesimulatingpulselidarsignalsinnoise.Thesimulationresultsshowthatthismethodcaneffectivelyidentifytheedgeofsignalanddetecttheweaklidarsignalburiedinnoises.

简介：Inthisworktwoaspectsoftheoryofframesarepresented:asidenecessaryconditiononirregularwaveletframesisobtained,anotherperturbationofwaveletandGaborframesisconsidered.Specifically,wepresenttheresultsobtainedonframestabilitywhenonedisturbsthemotherofwaveletframe,ortheparameterofdilatation,andinGaborframeswhenthegeneratingfunctionortheparameteroftranslationareperturbed.Inallcasesweworkwithoutdemandingcompactnessofthesupport,neitheronthegeneratingfunction,noronitsFouriertransform.

简介：Areviewoftheadvanceinthetheoryofwaveletanalysisinrecentyearsisgiven.

简介：这份报纸从与决定因素卤2的一个膨胀矩阵联系的框架multiresolution分析(FMRA)探讨小浪框架的构造。决定因素卤2的膨胀矩阵能根据不可分的类似作为六个班被分类。在这份报纸，为他们的四个班，从FMRA的小浪框架的构造被获得，并且，作为例子，香农类型小浪框架被构造，它在某感觉为他们的optimality有独立价值。关键词FMRA-FMRA小浪框架-不可分的类似先生(2000)题目分类42C40由训练北京(20051D0501522)的基础的优秀才能支持了

简介：Thispaperpresentssomeresultsoftherelationbetweenwavelettransformandfractaltransform.Thewavelettransformoftheattractoroffractaltransformpossesestranslationalandscaleinvariance.Sowespeedthefractalimageencodingbytestingtheinvarianceofthewavelettransformappropriateforimageencoding.Theclassficationschemeofrangeblocksbywavelettransformisgiveninthispaper.

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简介：Wavelettransformisaparticularlyusefultooltocharacterizetran-sientphenomenasuchaswavebreaking.Inthispaper,weapplywavelettransformtothedetectionandquantificationofthebreakingwaves.Weuseanewmethodthatusesthelocalpropertiesofwavelettransformtodetectandquantifythebreak-ingwavesandgivesomenewbreakingcriteria.Bycomparingthismethodwiththeclassicmethod,wefindthatwavelettransformisveryeffectiveinthedetectionofbreakingwaves.Withwavelettransform,asetofmeasuredwindwavedataisinves-tigated.Theresultshaverevealedsomepreviouslyunknownphenomenaaboutwavebreaking.

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简介：Inthispaper,alargeclassofndimensionalorthogonalandbiorthognalwaveletfilters(lowpassandhighpass)arepresentedinexplicitexpression.Wealsocharacterizeorthogonalfilterswithlinearphaseinthiscase.Someexamplesarealsogiven,includingnonseparableorhogonalandbiorthogonalfilterswithlinearphase.

简介：Thewavelettransformhasremarkableadvantagesandwideapplicationsindenoisingbecauseofitscharacteristicofgoodtime-frequency.Basedontheanalysisoftraditionalwaveletdenoisingmethods,whicharebasedonFouriertransform,animprovedmethodisproposed.ItovercomestheshortcomingsofthetraditionalFourierdenoisingmethod.Inthispaper,thedenoisingproceduresareintroducedrespectivelybasedonthewavelettransformandthemethodofconnectingthewaveletthresholdwiththewaveletbasisisadopted.ThroughMatlabsimulationandconcretedata,itarrivesattheconclusionthatthemethodofsignaldenoisingbasedonthewavelettransformisobviouslymoreeffectiveandbetterthanthetraditionalmethodbasedonFouriertransform.

简介：这份报纸在与2瑵?联系的bidimensionalmultiresolution分析的一个班的背景探讨aliasing错误?胴吗？？

简介：Inthispaper,weintroducematrix-valuedmultiresolutionanalysisandmatrix-valuedwaveletpackets.Aprocedurefortheconstructionoftheorthogonalmatrix-valuedwaveletpacketsispresented.Thepropertiesofthematrix-valuedwaveletpacketsareinvestigated.Inparticular,aneworthonormalbasisofL2(R,Cs×s)isobtainedfromthematrix-valuedwaveletpackets.

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简介：Astherearelotsofnon-linearsystemsintherealengineering,itisveryimportanttodomoreresearchesonthemodelingandpredictionofnon-linearsystems.Basedonthemulti-resolutionanalysis(MRA)ofwavelettheory,thispapercombinedthewavelettheorywithneuralnetworkandestablishedaMRAwaveletnetworkwiththescalingfunctionandwaveletfunctionasitsneurons.Fromtheanalysisinthefrequencydomain,theresultsindicatedthatMRAwaveletnetworkwasbetterthanotherwaveletnetworksintheabilityofapproachingtothesignals.AnessentialresearchwascarriedoutonmodelingandpredictionwithMRAwaveletnetworkinthenon-linearsystem.Usingthelengthwiseswaydatareceivedfromtheexperimentofshipmodel,amodelofofflinepredictionwasestablishedandwasappliedtotheshort-timepredictionofshipmotion.Thesimulationresultsindicatedthattheforecastingmodelimprovedthepredictionprecisioneffectively,lengthenedtheforecastingtimeandhadabetterpredictionresultsthanthatofARlinearmodel.TheresearchindicatesthatitisfeasibletousetheMRAwaveletnetworkintheshort-timepredictionofshipmotion.

简介：Anewmethodofshort-termforecastingforwaterconsumptioninmunicipalsupplywaternetworksbasedonwavelettransformationisintroduced.Bywaveletdecomposingcommonlyusedinthesignalfield,waterconsumptionperhourisdecomposedintomanyseries.Trenditem,cycleitemandrandomitemareseparatedfromtheoriginaltimeseriesinthisway.Thenbyanalyzing,buildingamodel,forecastingeveryseriesandcomposingtheresults,theforecastingvalueoftheoriginalconsumptionisreceived.Simulationresultsshowthatthisforecastingmethodisfasterandmoreaccurate,ofwhichtheerrorislessthan20%,indicatingthatthewaveletanalyticalmethodispracticable.

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简介：Researchinterestinmulti-frameSuperresolutionhasrisensubstantiallyinrecentyears.ThispaperpresentsamodifiedProjectionOntoConvexSet(POCS)superresolutionmethodbasedonwavelettransform.Themethodanalyzestheimageformationmodelfromwaveletmultiresolutionanalysispointofviewanddefinesanclosedconvexsetanditscorrespondingprojectionbasedonwavelettransform.Aniterativeprocedureisutilizedtoreducetheestimatederrorsoftheresultimage,andthisguaranteestheestimatedimagetolayintheintersectionofdifferentconvexsets,thusproducesahighresolutionimagewithareducederror.Theeffectivenessofthealgorithmisdemonstratedbyexperimentalresults.