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簡介：中文中文10700字出處出處YINLY,XIAOH,MADDUXTHYDROANDMORPHODYNAMICMODELINGOFBREAKINGSOLITARYWAVESOVERAFINESANDBEACHPARTIEXPERIMENTALSTUDYJMARINEGEOLOGY,2010,2693107118海洋地質(zhì)學(xué)海洋地質(zhì)學(xué)在一細(xì)沙海灘上對破碎孤立波的動態(tài)模擬（第一部分實驗研究在一細(xì)沙海灘上對破碎孤立波的動態(tài)模擬（第一部分實驗研究研究人員YINLUYOUNG、HENGXIAO、TIMOTHYMADDUX三位教授,他們分別隸屬于以下工作機(jī)構(gòu)1DEPARTMENTOFNAVALARCHITECTUREANDMARINEENGINEERING,UNIVERSITYOFMICHIGAN,ANNARBOR,MI48109,UNITEDSTATES2DEPARTMENTOFCIVILANDENVIRONMENTALENGINEERING,PRINCETONUNIVERSITY,PRINCETON,NJ08544,UNITEDSTATES3OHHINSDALEWAVERESEARCHLABORATORY,OREGONSTATEUNIVERSITY,CORVALLIS,OR97331,UNITEDSTATES關(guān)鍵詞關(guān)鍵詞海嘯、孤立波、泥沙輸移、移動基床、動態(tài)模擬、波浪泥沙相互作用摘要這項工作的目的有兩個（1）通過在一細(xì)沙海灘上對破碎孤立波的物理模擬來研究沿海地區(qū)內(nèi)影響海嘯侵蝕和沉積作用機(jī)制的原理；（2）提供實驗數(shù)據(jù)來驗證數(shù)值模型以預(yù)測海嘯的侵蝕和沉積過程。該實驗在長、寬、高分別為488米、216米、21米的風(fēng)洞造波水槽中進(jìn)行。建造水槽的目的是用來觀察附近的海岸線自由表面高程，跨岸速度，懸浮泥沙濃度，垂直和跨岸孔隙壓力梯度，和形態(tài)變化。此外，沉積物和波浪的相互作用，通過水下攝像機(jī)觀察。實驗結(jié)果被系統(tǒng)的分析以研究波浪破碎，孔爬高，波下跌，波浪作用下孔隙水壓力變化等等對海嘯侵蝕和沉積過程的作用。研究表明暴跌于到達(dá)海岸線之前的一層薄薄的水上的波浪沒有造成太大的沉積物懸浮，但是直接沖擊海灘的水射流夾帶大量的沙子。懸浮泥沙隨后被水動力推高至斜坡，同時破碎波轉(zhuǎn)化為一個湍流孔。小塊凈沉積區(qū)在最大爬高點附近被觀察到，該點流速和水深均接近零。在以厚水流形式出現(xiàn)的波下跌的過程中有相當(dāng)數(shù)量的沉積物運輸，這導(dǎo)致海濱坡面和海灘的凈侵蝕。臨近波下跌結(jié)束時在破碎區(qū)形成了一次水躍，造成大部分懸浮泥沙沉積在波浪破碎區(qū)。因此，在一傾斜適宜的細(xì)沙海灘的破碎孤立波能導(dǎo)致海濱坡面和海灘的凈侵蝕以及向海方向最大偏移點一小區(qū)域的凈沉淀和波浪破碎區(qū)的凈沉淀。1簡介簡介眾所周知，海嘯在沿海地區(qū)可以推移大量沉積物和產(chǎn)生顯著的形態(tài)學(xué)變化。由此產(chǎn)生的沖刷破壞，可以破壞建筑物，道路，堤壩，地下管線以及其他沿海結(jié)構(gòu)。因此，了解和預(yù)測與海嘯息息相關(guān)的地貌變化十分關(guān)鍵，以指導(dǎo)今后海岸線和沿海基礎(chǔ)設(shè)施的規(guī)劃，設(shè)計和開發(fā)。同樣重要的是要了解海嘯侵蝕和沉積過程，以根據(jù)海嘯沉積記錄推斷出過去海嘯發(fā)生的頻率和強(qiáng)度。本文的目標(biāo)是（1）通過在一適宜細(xì)沙海灘上對破碎孤立波的物理模擬建模來研究沿海地區(qū)內(nèi)影響海嘯侵蝕和沉積作用機(jī)制的原理；（2）提供實驗數(shù)據(jù)來驗證數(shù)值模型以預(yù)測海嘯沙灘上，孤立波（比深80厘米的海邊高出216厘米）被用來模擬海嘯。海灘最初被暴露于8段正孤立波下，隨后它被重建到初始112坡度并且暴露于8段負(fù)孤波之下。相比于正波運行，他們發(fā)現(xiàn)，負(fù)孤立波擁有較小和較慢的波爬高以及較弱的回流，因為爬高在由負(fù)波自由面斜坡引起的向海流的情況下得到加強(qiáng)。此外，正孤立波導(dǎo)致前灘侵蝕和沉淀物在波下跌時向海中移近，而負(fù)孤波導(dǎo)致前灘沉淀和波浪破碎點附近的侵蝕。他們的實驗研究為深化波形對侵蝕和沉積模式的影響提供了獨特的見解，但沒有足夠的數(shù)據(jù)捕獲瞬態(tài)侵蝕沉積的機(jī)制，因為泥沙通量率和孔隙壓力梯度不能得到測量。2目的目的為了提高對沿海地帶海嘯的侵蝕和沉積機(jī)制的理解，需要額外的控制實驗來探討波爬高和波下跌過程中各種短暫效應(yīng)的重要性。因此，進(jìn)行了一項大規(guī)模的實驗研究，來探究跨岸海嘯細(xì)沙輸沙和一適宜細(xì)沙海灘的侵蝕/沉積剖面。我們采取了傳統(tǒng)的把海嘯建模為一個孤立波的方法以簡化物理過程。因為大多數(shù)海嘯在到到達(dá)岸邊時波浪就已經(jīng)破碎，所以我們的研究重心放在破碎的孤立波上。3物理建模物理建模31建立實驗建立實驗實驗在美國俄勒岡州立大學(xué)的OHHINSDALE波浪研究實驗室中的海嘯盆地進(jìn)行。盆地尺寸的長、寬、高分別為488米、265米、21米。伴隨聯(lián)接系統(tǒng)和造波機(jī)的盆地的平面視圖如圖1。為了僅僅關(guān)注跨岸輸沙，盆地內(nèi)建成一個二維水槽，正是圖1中輕陰影區(qū)域。圖1用以實驗的海嘯波盆地，為該實驗專門修建的2維水槽的細(xì)節(jié)（輕陰影區(qū)域）見圖2。水槽尺寸的長、寬、高分別為488米、216米、21米。所有儀器都部署在這個水槽中。水槽的尺寸和傳感器的詳細(xì)信息如圖2所示。

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簡介：HYDROANDMORPHODYNAMICMODELINGOFBREAKINGSOLITARYWAVESOVERAFINESANDBEACHPARTIEXPERIMENTALSTUDYYINLUYOUNGA,?,HENGXIAOB,TIMOTHYMADDUXCADEPARTMENTOFNAVALARCHITECTUREANDMARINEENGINEERING,UNIVERSITYOFMICHIGAN,ANNARBOR,MI48109,UNITEDSTATESBDEPARTMENTOFCIVILANDENVIRONMENTALENGINEERING,PRINCETONUNIVERSITY,PRINCETON,NJ08544,UNITEDSTATESCOHHINSDALEWAVERESEARCHLABORATORY,OREGONSTATEUNIVERSITY,CORVALLIS,OR97331,UNITEDSTATESABSTRACTARTICLEINFOARTICLEHISTORYRECEIVED12DECEMBER2008RECEIVEDINREVISEDFORM29NOVEMBER2009ACCEPTED13DECEMBER2009AVAILABLEONLINE22DECEMBER2009COMMUNICATEDBYJTWELLSKEYWORDSTSUNAMISOLITARYWAVESEDIMENTTRANSPORTMOBILEBEDMORPHODYNAMICMODELINGWAVE–SOILINTERACTIONTHEOBJECTIVESOFTHISWORKARE1TOEXAMINETHEMECHANISMSTHATINFLUENCETSUNAMIEROSIONANDDEPOSITIONMECHANISMSINTHELITTORALZONEVIAPHYSICALSIMULATIONSOFBREAKINGSOLITARYWAVESOVERAFINESANDBEACH,AND2TOPROVIDEEXPERIMENTALDATAFORVALIDATIONOFNUMERICALMODELSTOPREDICTTSUNAMIEROSIONANDDEPOSITIONPROCESSESTHEEXPERIMENTSWERECARRIEDOUTINA488M216M21MWAVEFLUMETHEFLUMEWASINSTRUMENTEDTOOBSERVEFREESURFACEELEVATIONS,CROSSSHOREVELOCITIES,SUSPENDEDSEDIMENTCONCENTRATIONS,VERTICALANDCROSSSHOREPOREPRESSUREGRADIENTSNEARTHESHORELINE,ANDMORPHOLOGICALCHANGESINADDITION,WAVE–SEDIMENTINTERACTIONSWEREOBSERVEDVIAUNDERWATERVIDEOCAMERASTHERESULTSARESYSTEMATICALLYANALYZEDTOINVESTIGATETHEROLESOFWAVEBREAKING,BORERUNUP,WAVEDRAWDOWN,ANDWAVEINDUCEDPOREPRESSUREVARIATIONSONTSUNAMIEROSIONANDDEPOSITIONPROCESSESTHESTUDIESSHOWEDTHATTHEWAVEPLUNGINGONATHINLAYEROFWATERPRIORTOREACHINGTHESHORELINEDIDNOTCAUSEMUCHSEDIMENTSUSPENSION,WHILETHEWATERJETIMPINGINGDIRECTLYONTHEBEACHENTRAINEDSUBSTANTIALAMOUNTSOFSANDTHESUSPENDEDSEDIMENTSWERESUBSEQUENTLYPUSHEDUPTHESLOPEBYFLUIDMOMENTUMASTHEBROKENWAVETRANSFORMEDTOATURBULENTBOREASMALLNETDEPOSITIONREGIONWASOBSERVEDNEARTHEMAXIMUMRUNUPPOINTWHEREBOTHTHEFLOWVELOCITYANDTHEWATERDEPTHWERENEARZEROASIGNIFICANTAMOUNTOFTHESEDIMENTTRANSPORTOCCURREDDURINGTHEWAVEDRAWDOWNINTHEFORMOFTHICKSHEETFLOW,WHICHRESULTEDINNETEROSIONOFTHESHOREFACEANDTHEBEACHAHYDRAULICJUMPFORMEDNEARTHEWAVEBREAKINGREGIONTOWARDTHEENDOFTHEDRAWDOWN,WHICHCAUSEDMOSTOFTHESUSPENDEDSANDTODEPOSITINTHEWAVEBREAKINGREGIONCONSEQUENTLY,BREAKINGSOLITARYWAVESOVERASLOPINGFINESANDBEACHLEDTONETEROSIONOFTHESHOREFACEANDTHEBEACH,NETDEPOSITIONINASMALLREGIONIMMEDIATELYSEAWARDOFTHEMAXEXCURSIONPOINT,ANDNETDEPOSITIONINTHEWAVEBREAKINGZONE?2009ELSEVIERBVALLRIGHTSRESERVED1INTRODUCTIONITISWELLKNOWNTHATTSUNAMISCANMOBILIZESUBSTANTIALAMOUNTOFSEDIMENTDEPOSITSANDPRODUCESIGNIFICANTMORPHOLOGICALCHANGESINCOASTALREGIONSTHERESULTINGSCOURDAMAGECANUNDERMINEBUILDINGFOUNDATIONS,ROADWAYS,EMBANKMENTS,UNDERGROUNDPIPELINES,ANDOTHERCOASTALSTRUCTURESTHUS,ITISCRUCIALTOUNDERSTANDANDTOPREDICTGEOMORPHICALCHANGESASSOCIATEDWITHTSUNAMISTOGUIDEFUTUREPLANNING,DESIGN,ANDDEVELOPMENTOFCOASTLINESANDCOASTALINFRASTRUCTURESITISALSOIMPORTANTTOUNDERSTANDTHETSUNAMIEROSIONANDDEPOSITIONPROCESSESINORDERTOINFERTHEFREQUENCYANDINTENSITYOFPASTTSUNAMISBASEDONSEDIMENTARYRECORDSTHEOBJECTIVESOFTHISPAPERARETO1EXAMINETHEMECHANISMSTHATINFLUENCETSUNAMIEROSIONANDDEPOSITIONINTHELITTORALZONEVIAPHYSICALSIMULATIONSOFBREAKINGSOLITARYWAVESOVERAFINESANDBEACH,AND2PROVIDEEXPERIMENTALDATAFORVALIDATIONOFNUMERICALMODELSTOPREDICTTSUNAMIEROSIONANDDEPOSITIONPROCESSES11TSUNAMIVSWINDGENERATEDWAVESTSUNAMIISGENERALLYDEFINEDASLONGPERIODWAVESGENERATEDBYANUNDERWATEREARTHQUAKE,SUBMARINELANDSLIDES,VOLCANICERUPTIONS,ORASTROIDIMPACTSDUETOTHEIRLONGPERIODS,TSUNAMISAREOFTENMODELEDASSOLITARYWAVESINPHYSICALANDTHEORETICALSTUDIESTHEHIGHFLOWVELOCITYUPTO20M/S,LARGEFLOWDEPTHUPTO30MORMORE,ANDLONGWAVEPERIODOFTHEORDEROFHUNDREDSTOTHOUSANDSOFSECONDSOFAMAJORTSUNAMICANERODE,SUSPENDANDTRANSPORTALARGEVOLUMEOFSEDIMENTOVERABROADREGIONUPTOSEVERALKILOMETERSINLANDUMITSUETAL,1993PARISETAL,2007SRINIVASALUETAL,2007OVERTHELASTFIFTYYEARS,THEMAJORITYOFPREVIOUSSTUDIESRELATEDTOSEDIMENTTRANSPORTANDSCOURFOCUSEDONSTEADY,UNIFORMFLOWENVIRONMENTSSUCHASAROUNDRIVERBEDSANDBRIDGEPIERSRECENTLY,RESEARCHHASALSOBEGUNONTHESTUDYOFSEDIMENTTRANSPORTANDSCOURAROUNDCOASTALAREASSUBJECTTOWINDGENERATEDWAVESEGKRAUSANDMARINEGEOLOGY2692010107–118DOIOFORIGINALARTICLE101016/JMARGEO200912008?CORRESPONDINGAUTHOREMAILADDRESSYLYOUNGUMICHEDUYLYOUNG00253227/–SEEFRONTMATTER?2009ELSEVIERBVALLRIGHTSRESERVEDDOI101016/JMARGEO200912009CONTENTSLISTSAVAILABLEATSCIENCEDIRECTMARINEGEOLOGYJOURNALHOMEPAGEWWWELSEVIERCOM/LOCATE/MARGEOHEREONDETAILSOFTHEEXPERIMENTANDRESULTSFROMOTHERWAVECONDITIONSWILLBEPRESENTEDINASEPARATEREPORT32INSTRUMENTATIONSIXTEENWAVEGAUGESWEREUSEDTOMEASURETHEWAVEPROFILES,OFWHICH12WERERESISTANCETYPEWAVEGAUGESWG,IMTECHINCANDFOURWEREULTRASONICWAVEGAUGESDS,FORDISTANCESONIC,SENIXCORP,TS30S11VTHERESISTANCETYPEWAVEGAUGESWEREDEPLOYEDSEAWARDOFTHESHORELINEFROMX10MTOX27MANDTHEULTRASONICWAVEGAUGESWEREINSTALLEDLANDWARDOFTHESHORELINE,FROMX28MTOX32MTHESPECIFICLOCATIONSARESHOWNINFIG2EIGHTPOREPRESSURESENSORSPPSDRUCK/GE,PDCR81WEREINSTALLEDNEARTHESHORELINEATX25MANDX27MRESPECTIVELY,WITHFOURVERTICALLYSTACKEDINEACHLOCATIONTHEPPSWEREEQUALLYSPACEDVERTICALLY,WITH15CMINTERVALS,ASSHOWNINFIG2BSEVENACOUSTICDOPPLERVELOCIM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簡介：IEEETRANSACTIONSONBIOMEDICALENGINEERING,VOL59,NO6,JUNE20121499AUTOMATICMOTIONANDNOISEARTIFACTDETECTIONINHOLTERECGDATAUSINGEMPIRICALMODEDECOMPOSITIONANDSTATISTICALAPPROACHESJINSEOKLEE,MEMBER,IEEE,DAVIDDMCMANUS,SNEHMERCHANT,ANDKIHCHON,SENIORMEMBER,IEEEABSTRACTWEPRESENTAREALTIMEMETHODFORTHEDETECTIONOFMOTIONANDNOISEMNARTIFACTS,WHICHFREQUENTLYINTERFERESWITHACCURATERHYTHMASSESSMENTWHENECGSIGNALSARECOLLECTEDFROMHOLTERMONITORSOURMNARTIFACTDETECTIONAPPROACHINVOLVESTWOSTAGESTHEFIRSTSTAGEINVOLVESTHEUSEOFTHEFIRSTORDERINTRINSICMODEFUNCTIONFIMFFROMTHEEMPIRICALMODEDECOMPOSITIONTOISOLATETHEARTIFACTS’DYNAMICSASTHEYARELARGELYCONCENTRATEDINTHEHIGHERFREQUENCIESTHESECONDSTAGEOFOURAPPROACHUSESTHREESTATISTICALMEASURESONTHEFIMFTIMESERIESTOLOOKFORCHARACTERISTICSOFRANDOMNESSANDVARIABILITY,WHICHAREHALLMARKSIGNATURESOFMNARTIFACTSTHESHANNONENTROPY,MEAN,ANDVARIANCEWETHENUSETHERECEIVER–OPERATORCHARACTERISTICSCURVEONHOLTERDATAFROM15HEALTHYSUBJECTSTODERIVETHRESHOLDVALUESASSOCIATEDWITHTHESESTATISTICALMEASURESTOSEPARATEBETWEENTHECLEANANDMNARTIFACTS’DATASEGMENTSWITHTHRESHOLDVALUESDERIVEDFROM15TRAININGDATASETS,WETESTEDOURALGORITHMSON30ADDITIONALHEALTHYSUBJECTSOURRESULTSSHOWTHATOURALGORITHMSAREABLETODETECTTHEPRESENCEOFMNARTIFACTSWITHSENSITIVITYANDSPECIFICITYOF9663AND9473,RESPECTIVELYINADDITION,WHENWEAPPLIEDOURPREVIOUSLYDEVELOPEDALGORITHMFORATRIALFIBRILLATIONAFDETECTIONONTHOSESEGMENTSTHATHAVEBEENLABELEDTOBEFREEFROMMNARTIFACTS,THESPECIFICITYINCREASEDFROM7366TO8504WITHOUTLOSSOFSENSITIVITY7448–7462ONSIXSUBJECTSDIAGNOSEDWITHAFFINALLY,THECOMPUTATIONTIMEWASLESSTHAN02SUSINGAMATLABCODE,INDICATINGTHATREALTIMEAPPLICATIONOFTHEALGORITHMSISPOSSIBLEFORHOLTERMONITORINGINDEXTERMSATRIALFIBRILLATIONAF,EMPIRICALMODEDECOMPOSITIONEMD,HOLTERRECORDING,MOTIONANDNOISEMNARTIFACTDETECTION,STATISTICALMETHODIINTRODUCTIONWEHAVERECENTLYDEVELOPEDANALGORITHMFORACCURATEANDREALTIMEDETECTIONOFATRIALFIBRILLATIONAFTHATISWELLSUITEDFORCONTINUOUSECGMONITORINGAPPLICATIONS1MANUSCRIPTRECEIVEDJANUARY21,2011REVISEDJUNE27,2011ANDOCTOBER25,2011ACCEPTEDNOVEMBER5,2011DATEOFPUBLICATIONNOVEMBER10,2011DATEOFCURRENTVERSIONMAY18,2012THISWORKWASFUNDEDINPARTBYTHEOFFICEOFNAVALRESEARCHWORKUNITUNDERGRANTN000140810244ASTERISKINDICATESCORRESPONDINGAUTHORJLEEISWITHTHEDEPARTMENTOFBIOMEDICALENGINEERING,WORCESTERPOLYTECHNICINSTITUTE,MA01609USAEMAILJINSEOKWPIEDUDDMCMANUSISWITHTHECARDIOLOGYDIVISION,DEPARTMENTSOFMEDICINEANDQUANTITATIVEHEALTHSCIENCES,UNIVERSITYOFMASSACHUSETTSMEDICALCENTER,WORCESTER,MA01605USAEMAILMCMANUSDUMMHCORGSMERCHANTISWITHTHESCOTTCARECORPORATION,CLEVELAND,OH44135USAEMAILSMERCHANTSCOTTCARECOMKHCHONISWITHTHEDEPARTMENTOFBIOMEDICALENGINEERING,WORCESTERPOLYTECHNICINSTITUTE,MA01609USAEMAILKICHONWPIEDUCOLORVERSIONSOFONEORMOREOFTHEFIGURESINTHISPAPERAREAVAILABLEONLINEATHTTP//IEEEXPLOREIEEEORGDIGITALOBJECTIDENTIFIER101109/TBME20112175729USEOFECGMONITORSEG,HOLTERMONITORSISCOMMONINTHEDIAGNOSISANDMANAGEMENTOFPATIENTSWITH,ORATRISKFOR,AF,GIVENTHEPAROXYSMAL,SHORTLIVED,ANDFREQUENTLYASYMPTOMATICNATUREOFTHISSERIOUSARRHYTHMIAMONITORINGFORAFISIMPORTANTBECAUSE,DESPITEOFTENBEINGPAROXYSMALANDASSOCIATEDWITHMINIMALORNOSYMPTOMS,AFISASSOCIATEDWITHSEVEREADVERSEHEALTHCONSEQUENCES,INCLUDINGSTROKE,HEARTFAILURE,ANDDEATH2OURTESTOFACCURACYOFTHEAFALGORITHMWASPERFORMEDONNOISEREMOVEDTESTDATABASES,WHICHALSOCONSISTEDOFHOLTERRECORDINGSCERTAINLY,MOTIONANDNOISEMNARTIFACTSARESIGNIFICANTDURINGHOLTERRECORDINGSANDCANLEADTOFALSEDETECTIONSOFAFCLINICIANSHAVECITEDMNARTIFACTSINAMBULATORYMONITORINGDEVICESASTHEMOSTCOMMONCAUSEOFFALSEALARMS,LOSSOFSIGNAL,ANDINACCURATEREADINGS3,4PREVIOUSCOMPUTATIONALEFFORTSHAVELARGELYRELIEDONMNARTIFACTREMOVAL,ANDSOMEOFTHEPOPULARMETHODSINCLUDELINEARFILTERING5,ADAPTIVEFILTERING6,7,WAVELETDENOISING8–10,ANDBAYESIANFILTERINGMETHODS11ONEMAINDISADVANTAGEOFTHEADAPTIVEFILTERINGMETHODSISTHATTHEYREQUIREAREFERENCESIGNAL,WHICHISPRESUMEDTOBECORRELATEDINSOMEWAYWITHTHEMNARTIFACTSFORMITIGATINGTHISLIMITATION,USEOFACCELEROMETERSTOOBTAINAREFERENCESIGNALHASRESULTEDINSOMESUCCESS12,13HOWEVER,THISAPPROACHHASNOTBEENAPPLIEDTOHOLTERMONITORSTHEWAVELETDENOISINGAPPROACHATTEMPTSTOSEPARATECLEANANDNOISYWAVELETCOEFFICIENTS,BUTITCANBEDIFFICULTTOUSESINCEITREQUIRESIDENTIFICATIONOFTHELOCATIONOFEACHECGMORPHOLOGYINCLUDINGTHEPANDTWAVES8–10BAYESIANFILTERINGREQUIRESESTIMATIONOFOPTIMALPARAMETERSUSINGANYVARIANTOFKALMANFILTERINGMETHODSEXTENDEDKALMANFILTER,EXTENDEDKALMANSMOOTHER,ORUNSCENTEDKALMANFILTER11THEMAINDISADVANTAGEOFTHEBAYESIANFILTERINGAPPROACHISTHEIMPROPERASSUMPTIONTHATNOISEHASANADDITIVEGAUSSIANPROBABILITYDENSITYFUNCTIONFURTHER,THEMETHODREQUIRESRPEAKLOCATIONSFOREACHCYCLEOFECGDATAWHILETHEAFOREMENTIONEDSIGNALPROCESSINGAPPROACHESHAVEBEENAPPLIED,THEYARENOTAPPROPRIATE,ANDCONSEQUENTLYMNARTIFACTSREMAINAKEYOBSTACLETOTHEACCURATEDETECTIONOFAFANDATRIALFLUTTER,WHICHISANEQUALLYPROBLEMATICARRHYTHMIAANOVELMETHODTOSEPARATECLEANECGPORTIONSFROMSEGMENTSWITHMNARTIFACTSINREALTIMEISURGENTLYNEEDEDFORMOREACCURATEDIAGNOSISANDTREATMENTOFCLINICALLYIMPORTANTATRIALARRHYTHMIASFOROURPAPER,THEAIMISTODETECTTHEPRESENCEOFMNARTIFACTSFORHOLTERAPPLICATIONS,THEREAREASUFFICIENTNUMBEROFCLEA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簡介：BEHAVIORALECONOMICSANDMACROECONOMICMODELSJOHNCDRISCOLLA,STEINARHOLDENB,?AFEDERALRESERVEBOARD,20THANDCONSTITUTIONAVENW,WASHINGTON,DC20551,USABDEPARTMENTOFECONOMICS,UNIVERSITYOFOSLO,BOX1095,BLINDERN,0317OSLO,NORWAYARTICLEINFOARTICLEHISTORYRECEIVED17SEPTEMBER2012ACCEPTED23MAY2014AVAILABLEONLINE18JUNE2014JELCLASSIFICATIONE2E3D8KEYWORDSBEHAVIORALMACROECONOMICSNEWKEYNESIANMODELABSTRACTOVERTHEPAST20YEARS,MACROECONOMISTSHAVEINCORPORATEDMOREANDMORERESULTSFROMBEHAVIORALECONOMICSINTOTHEIRMODELSWEARGUETHATDOINGSOHASHELPEDFIXEDDEFICIENCIESWITHSTANDARDAPPROACHESTOMODELINGTHEECONOMYFOREXAMPLE,THECOUNTERFACTUALABSENCEOFINERTIAINTHESTANDARDNEWKEYNESIANMODELOFECONOMICFLUCTUATIONSWESURVEYEFFORTSTOUSEBEHAVIORALECONOMICSTOIMPROVESOMEOFTHEUNDERPINNINGSOFTHENEWKEYNESIANMODELSPECIFICALLY,CONSUMPTION,THEFORMATIONOFEXPECTATIONSANDDETERMINATIONOFWAGESANDEMPLOYMENTTHATUNDERLIEAGGREGATESUPPLY,ANDTHEPOSSIBILITYOFMULTIPLEEQUILIBRIAANDASSETPRICEBUBBLESWEALSODISCUSSMOREBROADLYTHEADVANTAGESANDDISADVANTAGESOFUSINGBEHAVIORALECONOMICSFEATURESINMACROECONOMICMODELS?2014ELSEVIERINCALLRIGHTSRESERVED1INTRODUCTIONOVERTHEPAST20YEARS,RESEARCHERSHAVEINCORPORATEDANINCREASINGNUMBEROFRESULTSFROMBEHAVIORALECONOMICSINTOMACROECONOMICMODELSTHEREARETWOMAINREASONSFORTHISCHANGEFIRST,ITHASBECOMECLEARTOMACROECONOMISTSTHATMODELSBASEDONASSUMPTIONSOFOPTIMIZINGBEHAVIORINMANYCASESHAVEDIFFICULTYACCOUNTINGFORKEYREALWORLDOBSERVATIONSHENCERESEARCHERSHAVEUSEDBEHAVIORALECONOMICSASSUMPTIONSWITHTHEAIMOFMAKINGTHEIRMODELPREDICTIONSBETTERFITTHEDATAEARLYATTEMPTSTODOTHISWERECRITICIZEDASBEINGADHOCTHEFORCEOFTHISCRITICISMHASBEENREDUCEDBYTHESECONDREASONFORINCORPORATINGBEHAVIORALECONOMICSRESULTSINTOMACROECONOMICSCOGNITIVEPSYCHOLOGISTSANDEXPERIMENTALECONOMISTSHAVEDOCUMENTEDANUMBEROFSYSTEMATICDEVIATIONSBETWEENTHEDECISIONSOFHUMANBEINGSANDTHOSEOFTHE‘‘ECONOMICMAN’’THEECONOMICSPROFESSIONHASWIDELY,THOUGHBYNOMEANSUNIVERSALLY,ACKNOWLEDGEDTHEEMPIRICALSUPPORTFORPUZZLESTHATCANBEEXPLAINEDBYBEHAVIORALFEATURESMOREOVER,BEHAVIORALFEATURESHAVEBEENINTRODUCEDINMANYPARTSOFMACROECONOMICSWHEREHAVETHESEDEVELOPMENTLEDUSWHICHASSUMPTIONSSHOULDONENOWMAKEWHENANALYZINGMACROECONOMICQUESTIONSTHEAIMOFTHISPAPERISTOPROVIDEASELECTIVESURVEYOFTHEIMPLICATIONSOFINSIGHTSFROMBEHAVIORALECONOMICSFORMACROECONOMICMODELSWEARGUETHATTHEINSIGHTSFROMBEHAVIORALECONOMICSHAVELEDTOIMPORTANTPROGRESSINOURUNDERSTANDINGOFMACROECONOMICPHENOMENABYALLOWINGUSTOEXPLAINMOREASPECTSOFREALWORLDBEHAVIORTHANWECOULDWITHTHEMORERESTRICTIVETHEORETICALFRAMEWORKTHATMOSTECONOMISTSHAVEBEENUSINGSOMEBEHAVIORALASSUMPTIONSTHATHAVEALREADYBEENIMPLEMENTEDINMACROECONOMICMODELS,SUCHASFAIRNESSCONSIDERATIONS,SEEMESPECIALLYPROMISINGTOUSINOTHERCASES,WESUSHTTP//DXDOIORG/101016/JJMACRO20140500401640704/?2014ELSEVIERINCALLRIGHTSRESERVED?CORRESPONDINGAUTHORTEL4722855156FAX4722855035EMAILADDRESSESJOHNCDRISCOLLFRBGOVJCDRISCOLL,STEINARHOLDENECONUIONOSHOLDENJOURNALOFMACROECONOMICS412014133–147CONTENTSLISTSAVAILABLEATSCIENCEDIRECTJOURNALOFMACROECONOMICSJOURNALHOMEPAGEWWWELSEVIERCOM/LOCATE/JMACROMONETARYPOLICY,ANDTHEASCURVE,RESPECTIVELY3THEMODELHASASTEADYSTATEOUTPUTGAPANDINFLATIONRATEOFZERO,ANDREALINTERESTRATEEQUALTOTHEWICKSELLIANLEVELINTHESHORTRUN,THEMODELCANBEUSEDTOTRACETHEEFFECTSOFSHOCKSONTHEOUTPUTGAP,INFLATION,ANDREALANDNOMINALINTERESTRATESWHILETHEMODELHASBEENSUCCESSFULINEXPLAININGBROADFEATURESOFTHERESPONSEOFREALVARIABLESTOMONETARYPOLICY,ITALSOHASANUMBEROFDEFICIENCIESONEKEYPROBLEMISTHATTHEMODELDISPLAYSALACKOFINERTIASHOCKSHAVEIMMEDIATEEFFECTS,WHICHDISSIPATEQUICKLYTOSEETHIS,NOTETHATASHOCKINPERIODTWILLONLYHAVEEFFECTSINTHATPERIODINSUBSEQUENTPERIODS,THELEVELSOFTHEENDOGENOUSVARIABLESONLYDEPENDONEACHOTHER,CURRENTSHOCKS,ANDEXPECTEDFUTURESHOCKSTHISCOMPLETELACKOFPERSISTENCEARISESFROMTHEABSENCEOFLAGGEDINFLATIONOROUTPUTGAPTERMSINTHEISORASEQUATIONSEITHERDIRECTLY,ORINDIRECTLYTHROUGHEXPECTATIONSWHICHMAYDEPENDONTHEMTHISPREDICTIONISSTRONGLYCONTRARYTOEMPIRICALEVIDENCETHAT,FOREXAMPLE,THEREALEFFECTSOFMONETARYPOLICYSHOCKSAREBOTHDELAYEDANDLONGLASTINGASECONDPROBLEM,NOTEDBYBALL1994ANDMANKIW2001,ISTHATTHEAGGREGATESUPPLYSCHEDULEIMPLIESTHATINFLATIONISEXPECTEDTOFALLINABOOM–ACCORDINGTO3,WHENTHEOUTPUTGAPYT0,PTETPTT1THISFEATUREISINCONSISTENTWITHEVIDENCESUPPORTINGTHENAIRU,THATINFLATIONINCREASESWHENOUTPUTISHIGHRELATIVETOTHENATURALRATEBALL1994LOOKSATTHISISSUEFROMTHEPERSPECTIVEOFCREDIBILITYOFTHECENTRALBANKHESHOWSTHATTHENEWKEYNESIANMODELSIMPLIESTHATCREDIBLEDISINFLATIONSSHOULDBEACCOMPANIEDBYEXPANSIONS,BUTPROVIDESEVIDENCETHATACTUALDISINFLATIONSHAVEBEENASSOCIATEDWITHRECESSIONSTHESEPROBLEMSHAVELEDTHOSEWHOWISHTOUSESUCHMODELSWITHANUNAPPEALINGCHOICEUSETHISMODELWITHTHEORETICALSUPPORTBUTEMPIRICALDEFICIENCIES,ORALTERTHEMODELSOTHATITBETTERFITSTHEDATASOMERESEARCHERSHAVETAKENTHELATTERCOURSEEGRUDEBUSCH2002APREFERABLESOLUTIONWOULDBETOFINDMODELSWITHMICROECONOMICSUPPORTWHICHFOLLOWTHEMACROECONOMICDATAFUHRERANDMOORE1995SUGGESTEDAMODELWHEREAGENTSCAREABOUTRELATIVEREALWAGESFORACRITIQUE,SEEHOLDENANDDRISCOLL,2003AMORECOMMONFORMULATIONISAHYBRIDMODEL,WHERESOMEAGENTSAREFORWARDLOOKINGANDOTHERAGENTSAREBACKWARDLOOKINGEGGALIANDGERTLER,1999WHILE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簡介：經(jīng)驗?zāi)Ｊ椒纸夂徒y(tǒng)計學(xué)方法下的動態(tài)HOLTER心電圖運動偽影檢測中文中文8200字，字，4600單詞，單詞，24萬英文字符萬英文字符出處出處LEEJ,MCMANUSDD,MERCHANTS,ETALAUTOMATICMOTIONANDNOISEARTIFACTDETECTIONINHOLTERECGDATAUSINGEMPIRICALMODEDECOMPOSITIONANDSTATISTICALAPPROACHESJIEEETRANSACTIONSONBIOMEDICALENGINEERING,2011,5961499506經(jīng)驗?zāi)Ｊ椒纸夂徒y(tǒng)計學(xué)方法下的動態(tài)HOLTER心電圖運動偽影檢測偽影檢測AUTOMATICMOTIONANDNOISEARTIFACTDETECTIONINHOLTERECGDATAUSINGEMPIRICALMODEDECOMPOSITIONANDSTATISTICALAPPROACHESJINSEOKLEE,MEMBER,IEEE,DAVIDDMCMANUS,SNEHMERCHANT,ANDKIHCHON,SENIORMEMBER,IEEE摘要我們提出一個用于實時檢測連續(xù)接收到運動（HOLTER）心電圖的運動噪聲偽影的方法。運動噪聲偽影檢測方法分為兩個階段第一階段涉及使用FIMF模式固有模態(tài)函數(shù)分解出內(nèi)在的運動偽影，因為他們廣泛的分布在高頻率部分。第二階段，使用三種統(tǒng)計學(xué)方法從FIMF固有模態(tài)函數(shù)時間序列中尋找運動偽影隨機(jī)性和變異性的特點香農(nóng)熵，均值和方差。然后我們使用從15名健康受試者接收到的動態(tài)心電圖特征曲線中計算出閾值，使用統(tǒng)計方法分離出純凈的數(shù)據(jù)段和運動（MN）偽影數(shù)據(jù)段。使用從15個心電數(shù)據(jù)段中提取的這15組閾值，然后再用我們的算法測試了30組健康受試者的數(shù)據(jù)進(jìn)行驗證。此外，使用我們開發(fā)的算法檢測心房顫動（AF）受試者被標(biāo)記為與運動噪聲偽影無關(guān)的數(shù)據(jù)段時，在沒有丟失敏感性7448–7462的條件下，六個被診斷為心房顫動（AF）的受試者的運動噪聲偽影特異性從7366上升到8504。最后，發(fā)現(xiàn)使用MATALAB代碼測試該算法的運行時間小于02秒，可以使用在動態(tài)實時的心電監(jiān)測中。關(guān)鍵詞心房顫動（AF），經(jīng)驗?zāi)Ｊ椒纸猓‥MD），動態(tài)心電圖記錄，運動噪聲（MN）偽影檢測，統(tǒng)計方法。1、介紹最近我們開發(fā)了一種實時監(jiān)測心房顫動（AF）患者心電圖的算法，這種算法能夠使用在實時監(jiān)測患者動態(tài)心電圖中。ECG信號監(jiān)測儀（如動態(tài)ECG信號）在診斷和疾病護(hù)理，如心房顫動（AF）等高頻率的陣發(fā)性、致命性的心律失常，動態(tài)ECG信號起著重要的作用2。心電監(jiān)測儀對于心房顫動（AF）的診斷是很重要的，盡管心房顫動（AF）經(jīng)常從良性的心律失常開始，但是心房顫動的危害性很大，會導(dǎo)致心臟衰竭，中風(fēng)，甚至死亡。我們使用去除噪聲后動態(tài)記錄的ECG數(shù)據(jù)來檢測心房顫動算法的正確性。當(dāng)然，因為心電數(shù)據(jù)檢測的過程中伴隨著運動偽影，可能導(dǎo)致檢測到的心房顫動（AF）數(shù)據(jù)出現(xiàn)誤差。有著多年臨床經(jīng)驗的醫(yī)師指出，動態(tài)心電檢測設(shè)備中運動偽影是造成心電信號丟失和誤差的最主要的原因。34目前的計算工作在很大程度上依賴于運動（MN）偽影消除，而常用的一些方法，包括線性濾波5，自適應(yīng)濾波6，小波去噪810，和貝葉斯濾波11。自適應(yīng)濾波最主要的一個缺點是他們需要一個被假定為與某種方式和運動（MN）經(jīng)驗?zāi)Ｊ椒纸夂徒y(tǒng)計學(xué)方法下的動態(tài)HOLTER心電圖運動偽影檢測4）從信號中減去DTXT?MT5）用D（T）替換XT，重復(fù)上述步驟直到D（T）變?yōu)榱憔颠^程。停止迭代后，D（T）便是FIMF。結(jié)果表明，在經(jīng)驗?zāi)Ｊ椒纸夥ǎ‥MD）的第一固有模態(tài)函數(shù)（FIMF）動態(tài)存在，雖然它們已通過一個高通濾波器濾波（HPF）20濾波。因此，并不奇怪在第一固有模態(tài)函數(shù)（FIMF）中包含動態(tài)噪音相關(guān)的任何及采樣數(shù)據(jù)21。被MN偽影損壞的ECG信號對以前的聲明仍然有效，例如我們觀察到的高通濾波信號〔參見圖。圖1（D）〕具有噪聲動態(tài)的特性。為了說明心電圖信號噪聲中存在第一固有模態(tài)函數(shù)（FIMF），我們顯示一段5秒長的ECG片段，從一個干凈和含噪聲的ECG段動態(tài)心電記錄第一固有模態(tài)函數(shù)（FIMF）示于圖1。該心電圖段記錄了SCOTTCARE公司的的RZ153系列心電記錄儀在采樣頻率為180HZ，屏幕分辨率為10位下的ECG信號。在圖1中（A）是沒有任何噪聲的純凈ECG信號，圖1（C）的則在MN偽影條件下的ECG信號。圖1（B）是干凈的ECG信號下的FIMF。1（D）代表噪聲信號的FIMF。由圖中可見，干凈的ECG段的FIMF具有周期性，而MN偽影損壞ECG段有強(qiáng)烈變化的不規(guī)則動態(tài)低幅度噪聲與無噪聲的ECG信號的FIMF相比。圖1第一固有模態(tài)函數(shù)（FIMF）基于干凈和噪聲提取的ECG信號。A干凈的ECG信號B干凈信號的FIMFC．含噪聲信號的ECGD噪聲信號的FIMF獲得第一固有模態(tài)函數(shù)（FIMF）之后，對其進(jìn)行進(jìn)一步的處理，因為它既有負(fù)值又有正值，可以并歸到一個單恒定的單位值。注意隨著心電圖信號振幅來自不同受試者中，誰也可能有不同的引線配置和傳感器擴(kuò)增，我們將其值標(biāo)準(zhǔn)化處理，計算FIMF的均方值。圖2顯示代表取平方后干凈的ECG信號參見圖1（A）的FIMF，以及含噪聲信號ECG參見（圖1的（B）。如圖2中所示，干凈的信號最大振幅參見圖2（A）是一個數(shù)量級比那些在MN損壞的ECG信號中更高中〔見圖2（B）〕，這表明通過一個閾值可以將這兩種類型的信號之進(jìn)行分離。

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簡介：中文中文18500字出處出處DRISCOLLJC,HOLDENSBEHAVIORALECONOMICSANDMACROECONOMICMODELSJJOURNALOFMACROECONOMICS,2014,41133147行為經(jīng)濟(jì)學(xué)和宏觀經(jīng)濟(jì)模型行為經(jīng)濟(jì)學(xué)和宏觀經(jīng)濟(jì)模型過去20年，宏觀經(jīng)濟(jì)學(xué)家越來越多地將行為經(jīng)濟(jì)學(xué)的結(jié)論加入他們的模型中，這樣做有助于彌補(bǔ)利用標(biāo)準(zhǔn)方法模擬經(jīng)濟(jì)而造成的缺陷，例如模擬經(jīng)濟(jì)動蕩的新凱恩斯模型缺少慣性。我們努力利用行為經(jīng)濟(jì)學(xué)來改善一些新凱恩斯模型的基礎(chǔ)內(nèi)容，特別是消費、總供給的基礎(chǔ)期望的形成和工資與就業(yè)的決定因素、多重均衡和資產(chǎn)價格泡沫的可能性。我們也廣泛討論了將行為經(jīng)濟(jì)學(xué)的特征引入宏觀經(jīng)濟(jì)模型所造成的利害。1介紹介紹過去20年，宏觀經(jīng)濟(jì)學(xué)家越來越多地將行為經(jīng)濟(jì)學(xué)的特征引入宏觀經(jīng)濟(jì)的模型中。原因有兩點。首先，宏觀經(jīng)濟(jì)學(xué)者意識到，基于最優(yōu)行為假定的模型在許多方面都難以解釋關(guān)鍵的實際現(xiàn)狀。因而，研究者利用行為經(jīng)濟(jì)學(xué)的假定來使他們的模型預(yù)測更加貼近于實際數(shù)據(jù)。剛開始這樣的嘗試被批評為很另類，而這些批評的壓力因為第二個原因的出現(xiàn)而減少了。第二個原因是認(rèn)知心理學(xué)家和實驗經(jīng)濟(jì)學(xué)家證實了現(xiàn)實中人們的決定與那些“經(jīng)“經(jīng)濟(jì)人濟(jì)人”存在許多偏差。很多經(jīng)濟(jì)難題能夠被行為特征解釋，這一事實的實證支持已經(jīng)得到經(jīng)濟(jì)學(xué)界的廣泛認(rèn)可，當(dāng)然并沒得到全部認(rèn)可。而且，行為特征已經(jīng)被引入到宏觀經(jīng)濟(jì)學(xué)的許多方面。這些發(fā)展將會把我們帶向何方呢當(dāng)一個人分析宏觀經(jīng)濟(jì)問題時應(yīng)該采取何種假設(shè)呢本篇文章的目的就是提供一個選擇性的探究，探究宏觀經(jīng)濟(jì)模型方面來自行為經(jīng)濟(jì)學(xué)的觀點啟示。我們強(qiáng)調(diào)，來自行為經(jīng)濟(jì)學(xué)的啟示已經(jīng)在理解宏觀經(jīng)濟(jì)現(xiàn)象方面取得了重大進(jìn)步。因為相比于許多經(jīng)濟(jì)學(xué)家曾經(jīng)使用的非?？量痰睦碚摽蚣?，行為經(jīng)濟(jì)學(xué)的啟示能讓我們解釋現(xiàn)實世界行為的更多方面。已經(jīng)應(yīng)用于宏觀經(jīng)濟(jì)模型的一些行為假設(shè)看起來很有應(yīng)用前景，如公平考量。另一方面，我們猜想，行為經(jīng)濟(jì)模型也被需用于解釋宏觀經(jīng)濟(jì)難題，比如經(jīng)濟(jì)波動的慣性表現(xiàn)。但是，我們并不能確定哪些行為假設(shè)是最好的。仍有一些其他的結(jié)果是由認(rèn)知心理造成的，但認(rèn)知心理的宏觀經(jīng)濟(jì)啟示還沒有被挖掘。將行為假設(shè)融入宏觀經(jīng)濟(jì)模型并非沒有問題。即使從認(rèn)知心理學(xué)和實驗經(jīng)濟(jì)學(xué)中得到了大量有關(guān)確定行為特征的微觀經(jīng)濟(jì)證據(jù)，我們?nèi)匀缓茈y知曉哪些特征是最貼近于宏觀經(jīng)濟(jì)模型的。比如，雖然大量證據(jù)表明宏觀經(jīng)濟(jì)消費行為存在慣性，但我們并不清楚這個慣性應(yīng)該被看作習(xí)慣養(yǎng)成的結(jié)果，還是應(yīng)該被看作消費的經(jīng)驗法則，還是應(yīng)該被看作其它什么。另一個公開的問題是宏觀經(jīng)濟(jì)模型是應(yīng)該引入行為特征，還是應(yīng)該引入來自標(biāo)準(zhǔn)經(jīng)濟(jì)模型的其它偏差，比如經(jīng)濟(jì)摩擦力，不完全信息或者代理問題。因此，需要做更多的研究來指導(dǎo)模型設(shè)定的選擇。基于宏觀經(jīng)濟(jì)學(xué)中行為經(jīng)濟(jì)學(xué)的廣泛影響，我們有必要收窄談?wù)摰姆秶?。我們聚焦于?jīng)濟(jì)波動，失業(yè)和儲蓄這些核心的宏觀領(lǐng)域，行為經(jīng)濟(jì)學(xué)的結(jié)論已經(jīng)深入地應(yīng)用于這些領(lǐng)域。作為一個組織原理，我們使用新凱恩斯模型的變型。雖然新凱恩斯模型被廣泛應(yīng)用于分析經(jīng)濟(jì)波動和評估不同財政政策的實際效力，它仍然有顯著的經(jīng)驗缺陷。彌補(bǔ)這些缺陷的努力主要集中于使用不同的方法來形成模型假設(shè)、期望、名義工資和價格制定。我們將會討論這些方面，通過對消費的探討來研究長期消費和儲蓄的問題，通過對工資和價格制定的探討來研究長期勞動市場問題。我們將會忽略關(guān)于財政、增長率和幸福的問題，因為多重均衡、信息的影響和資產(chǎn)市場泡沫這三方面與經(jīng)濟(jì)波動相關(guān)，所以我們只會對這三個方面進(jìn)行一個簡短的談?wù)?。在每一個主題中，我們都將討論基于行為假定的關(guān)鍵創(chuàng)新，也包括非行為假定的選擇。遺憾的是，由于空間有限，論文內(nèi)容也必須在被覆蓋的專題內(nèi)進(jìn)NAIRU的證據(jù)相矛盾。該證據(jù)是當(dāng)產(chǎn)出相對高于自然率水平時，通貨膨脹就會增加。貝爾從中央銀行的可信度視角來看待這個問題。他表示新凱恩斯模型意味著可信的通貨緊縮應(yīng)該伴隨著膨脹，但是現(xiàn)實證據(jù)表明實際通貨緊縮與衰退相聯(lián)系。這些問題已經(jīng)使得希望使用這個模型的人面臨一個糾結(jié)的選擇或者在理論的支持下使用這個模型但是面臨實證的缺陷，或者改變模型使其更貼近于數(shù)據(jù)。一些研究者已經(jīng)采取了后一種做法，比如魯?shù)喜际病Ｒ粋€較好的解決辦法是找到一個微觀經(jīng)濟(jì)支持的符合宏觀經(jīng)濟(jì)數(shù)據(jù)的模型。菲雷爾和摩爾建議了一個模型，在該模型中，經(jīng)濟(jì)人關(guān)心相關(guān)的實際工資。一個更加普遍的構(gòu)想是混合模型，該模型中一部分經(jīng)濟(jì)人是有遠(yuǎn)見的，而另一部分經(jīng)濟(jì)人是短視的。雖然這個模型很明顯具有吸引人的要素，但它仍然受到嚴(yán)厲的批判。它被認(rèn)為與證據(jù)相矛盾，尤其是有遠(yuǎn)見的經(jīng)紀(jì)人那部分被稱為實證無效。越來越多的研究者轉(zhuǎn)向行為經(jīng)濟(jì)學(xué)來尋找微觀經(jīng)濟(jì)基礎(chǔ)，進(jìn)而創(chuàng)造更好的宏觀經(jīng)驗預(yù)測。其中大部分是探索不同的消費模型，探索期望產(chǎn)生的不同思考方式或者探索決定名義工資的不同模型。我們在接下來的兩部分探討這三個主題，并且進(jìn)一步利用消費的討論來檢驗長期消費和儲蓄的選擇。3消費消費31消費歐拉方程消費歐拉方程和短期行為和短期行為行為經(jīng)濟(jì)學(xué)有著最大影響的領(lǐng)域之一就是家庭消費的研究?；魻査珜?dǎo)的標(biāo)準(zhǔn)消費歐拉方程的方法已經(jīng)不能夠解釋現(xiàn)實行為的關(guān)鍵領(lǐng)域。根據(jù)長期收入假說，消費應(yīng)該是一個純粹前瞻性的變量，該變量取決于消費者預(yù)期的包含未來勞動收入的凈財富。因此,消費應(yīng)該對未來預(yù)期收入的新信息立刻回應(yīng),但是會更少響應(yīng)當(dāng)前可支配收入的變化,只要后者沒有透露關(guān)于未來收入的信息。然而,經(jīng)驗證據(jù)表明,消費更少的回應(yīng)新信息,結(jié)果是,消費者會表現(xiàn)出“過度平滑”坎貝爾和迪頓,1989。消費者也會對當(dāng)前收入“過于敏感”。這些結(jié)果都已被達(dá)菲通過實驗證實。然而，還應(yīng)該指出的是，一些實驗還發(fā)現(xiàn)了其它關(guān)于這一理論的預(yù)測。比如，消費會對折扣或者利率的改變產(chǎn)生反應(yīng)，這已經(jīng)得到實驗支持。對過度平滑的一個傳統(tǒng)的行為解釋是消費者習(xí)慣的養(yǎng)成。如波拉克1970，亞伯1990和菲雷爾2000。習(xí)慣的養(yǎng)成起源于稟賦效應(yīng)，稟賦效應(yīng)是一個認(rèn)知心理學(xué)實驗的結(jié)果，該實驗中，個人所擁有的財富物品對其擁有者的價值會有所增長，如勒文施泰因和艾德勒1995表明的那樣。稟賦效應(yīng)廣泛用于宏觀經(jīng)濟(jì)學(xué)它的使用加快了行為經(jīng)濟(jì)學(xué)在過去的幾十年里的進(jìn)步,研究也表明,它對其他經(jīng)濟(jì)問題也有重要意義,如股權(quán)溢價之謎康斯坦丁尼德斯,1990。這些模型表明，基于新凱恩斯IS曲線的消費歐拉方程將消費比率和習(xí)慣與臨近時期的參考水平聯(lián)系了起來，等式1將會含有滯后的產(chǎn)出期。以此為基礎(chǔ)的另一種新凱恩斯曲線，通過改變消費的參考水平，能夠加強(qiáng)產(chǎn)出波動影響的持續(xù)性。采用這個方法提高了財政政策標(biāo)準(zhǔn)模型的經(jīng)驗關(guān)聯(lián)性。菲雷爾發(fā)現(xiàn)包括習(xí)慣形成在內(nèi)，在某種意義上,消費者的效用在一定程度上取決于相對于過去消費量的當(dāng)前消費,斯麥茨和沃特斯也在他們的模型中使用了同樣的方法。雖然習(xí)慣的形成在現(xiàn)代宏觀經(jīng)濟(jì)研究的許多方面扮演了重要的角色，但經(jīng)驗上的證據(jù)還是混雜的。戴南2000發(fā)現(xiàn)在美國家庭中沒有證據(jù)支持習(xí)慣形成,而愛麗絲和塔帕2010發(fā)現(xiàn)了一些證據(jù)支持荷蘭家庭存在習(xí)慣形成,但力度相當(dāng)小。福薩洛和特科沃斯基2011在核對美國家庭賬目的基礎(chǔ)上分析了消費行為，結(jié)果也沒得出習(xí)慣形成的證據(jù)。然而，作者們解釋到，他們的發(fā)現(xiàn)若作為證據(jù)來支持由坎貝爾和曼昆提出的“經(jīng)驗法則”消費類型是具有流動性約束的。鑒于習(xí)慣形成的證據(jù)混雜,其在宏觀經(jīng)濟(jì)模型的使用可能更多的被視為一種分析慣性產(chǎn)生的便利方式，而不是作為一個消費的微觀經(jīng)濟(jì)基礎(chǔ)的真正反映。并且，還有很多替代習(xí)慣形成的分析方式。帕格爾表明，基于損失厭惡的期望模型能夠解釋消費對當(dāng)前收入的過量敏感性。加利等人2007把經(jīng)驗法則消費者融入一個改進(jìn)的新凱恩斯模型中,結(jié)果表明,這

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