雨课堂学堂在线学堂云《Artificial Neural Networks Theory and Its Applications（长安）》单元测试考核答案

第1题Biologicalneuronscanbedividedintosensoryneurons,motorneuronsand（）accordingtotheirfunctions.APseudounipolarneuralnetworksBbipolarneuronsCmultipolarneuronsDinterneurons第2题Neuronsandglialcellsarethetwomajorpartsofthenervoussystem.第3题Neuronsarehighlypolarizedcells,whicharemainlycomposedoftwoparts:thecellbodyandthesynapse.第4题Thehumanbrainisanimportantpartofthenervoussystem,whichcontainsmorethan86billionneurons.Itisthecentralinformationprocessingorganizationofhumanbeings.第5题Synapseistheplacewhereneuronsconnectinfunction.Itiscomposedofpresynapticmembrane,synapticspaceandpostsynapticmembrane.第1题In1989,Mead,thefatherofVLSI,publishedhismonograph"()",inwhichageneticneuralnetworkmodelbasedonevolutionarysystemtheorywasproposed.APerceptrons:AnIntroductiontoComputationalGeometryBLearningMachinesCAnalogVLSIandNeuralSystemsDJournalNeuralNetworks第2题In1989,YannLecunproposedconvolutionalneuralnetworkandappliedittoimageprocessing,whichshouldbetheearliestapplicationfieldofdeeplearningalgorithm.第3题In1954,Eccles,aneurophysiologistattheUniversityofMelbourne,summarizedtheprincipleofDale,aBritishphysiologist,that"eachneuronsecretesonlyonekindoftransmitter".第4题In1972,ProfessorKohonenofFinlandproposedaself-organizingfeaturemap(SOFM)neuralnetworkmodel.第5题Predictionandevaluationisanactivityofscientificcalculationandevaluationofsomecharacteristicsanddevelopmentstatusofthingsoreventsinthefutureaccordingtotheknowninformationofobjectiveobjects.TestforChapter3第1题Thefunctionoftransferfunctioninneuronsistogetanewmappingoutputofsummeraccordingtothespecifiedfunctionrelationship,andthencompletesthetrainingofartificialneuralnetwork.第2题Thedeterminantchangessignwhentworows(ortwocolumns)areexchanged.Thevalueofdeterminantiszerowhentworows(ortwocolumns)aresame.第3题Therearetwokindsofphenomenaintheobjectiveworld.Thefirstisthephenomenonthatwillhappenundercertainconditions,whichiscalledinevitablephenomenon.Thesecondkindisthephenomenonthatmayormaynothappenundercertainconditions,whichiscalledrandomphenomenon.第4题LogarithmicS-typetransferfunction,namelySigmoidfunction,isalsocalledS-shapedgrowthcurveinbiology.第5题Rectifiedlinearunit(ReLU),similartotheslopefunctioninmathematics,isthemostcommonlyusedtransferfunctionofartificialneuralnetwork.TestforChapter4第1题Theperceptronlearningalgorithmisdrivenby（

）,sothestochasticgradientdescentmethodisusedtooptimizethelossfunction.

AmaximumBminimumCmisclassificationDcorrect第2题Perceptronisasingle-layerneuralnetwork,orneuron,whichisthesmallestunitofneuralnetwork.第3题Whentheperceptronislearning,eachsamplewillbeinputintotheneuronasastimulus.Theinputsignalisthefeatureofeachsample,andtheexpectedoutputisthecategoryofthesample.Whentheoutputisdifferentfromthecategory,wecanadjustthesynapticweightandbiasvalueuntiltheoutputofeachsampleisthesameasthecategory.第4题Ifthesymmetrichardlimitfunctionisselectedforthetransferfunction,theoutputcanbeexpressedasy=+1n≥0ory=-1n＜0，Iftheinnerproductoftherowvectorandtheinputvectorintheweightmatrixisgreaterthanorequalto-b,theoutputis1,otherwisetheoutputis-1.第5题Thebasicideaofperceptronlearningalgorithmistoinputsamplesintothenetworkstepbystep,andadjusttheweightmatrixofthenetworkaccordingtothedifferencebetweentheoutputresultandtheidealoutput,thatistosolvetheoptimizationproblemoflossfunctionL(w,b).

TestforChapter5第1题TheoutputofBPneuralnetworkis（）ofneuralnetwork.Atheoutputofthelastlayer

BtheinputofthelastlayerCtheoutputofthesecondlayerDtheinputofthesecondlayer第2题BPneuralnetworkhasbecomeoneofthemostrepresentativealgorithmsinthefieldofartificialintelligence.Ithasbeenwidelyusedinsignalprocessing,patternrecognition,machinecontrol(expertsystem,datacompression)andotherfields.第3题In1974,PaulWerbosofthenaturalsciencefoundationoftheUnitedStatesfirstproposedtheuseoferrorbackpropagationalgorithmtotrainartificialneuralnetworksinhisdoctoraldissertationofHarvardUniversity,anddeeplyanalyzedthepossibilityofapplyingittoneuralnetworks,effectivelysolvingtheXORloopproblemthatsinglesensorcannothandle.第4题InthestandardBPneuralnetworkalgorithmandmomentumBPalgorithm,thelearningrateisaconstantthatremainsconstantthroughoutthetrainingprocess,andtheperformanceofthelearningalgorithmisverysensitivetotheselectionofthelearningrate.第5题L-Malgorithmismainlyproposedforsuperlargescaleneuralnetwork,anditisveryeffectiveinpracticalapplication.TestforChapter6第1题RBFneuralnetworkisanovelandeffectivefeedforwardneuralnetwork,whichhasthebestlocalapproximationandglobaloptimalperformance.第2题Atpresent,RBFneuralnetworkhasbeensuccessfullyappliedinnonlinearfunctionapproximation,timeseriesanalysis,dataclassification,patternrecognition,informationprocessing,imageprocessing,systemmodeling,controlandfaultdiagnosis.第3题ThebasicideaofRBFneuralnetworkistouseradialbasisfunctionasthe"basis"ofhiddenlayerhiddenunittoformhiddenlayerspace,andhiddenlayertransformsinputvector.Theinputdatatransformationoflowdimensionalspaceismappedintohigh-dimensionalspace,sothattheproblemoflinearseparabilityinlow-dimensionalspacecanberealizedinhigh-dimensionalspace.第4题ForthelearningalgorithmofRBFneuralnetwork,thekeyproblemistodeterminethecenterparametersoftheoutputlayernodereasonably.第5题ThemethodofselectingthecenterofRBFneuralnetworkbyself-organizinglearningistoselectthecenterofRBFneuralnetworkbyk-meansclusteringmethod,whichbelongstosupervisedlearningmethod.TestforChapter7第1题Intermsofalgorithm,ADALINEneuralnetworkadoptsW-Hlearningrule,alsoknownastheleastmeansquare(LMS)algorithm.Itisdevelopedfromtheperceptronalgorithm,anditsconvergencespeedandaccuracyhavebeengreatlyimproved.第2题ADALINEneuralnetworkhassimplestructureandmulti-layerstructure.Itisflexibleinpracticalapplicationandwidelyusedinsignalprocessing,systemidentification,patternrecognitionandintelligentcontrol.第3题WhentherearemultipleADALINEinthenetwork,theadaptivelinearneuralnetworkisalsocalledMadalinewhichmeansmanyAdalineneuralnetworks.第4题Thealgorithmusedinsingle-layerADALINEnetworkisLMSalgorithm,whichissimilartothealgorithmofperceptron,andalsobelongstosupervisedlearningalgorithm.第5题Inpracticalapplication,theinverseofthecorrelationmatrixandthecorrelationcoefficientarenoteasytoobtain,sotheapproximatesteepestdescentmethodisneededinthealgorithmdesign.Thecoreideaisthattheactualmeansquareerrorofthenetworkisreplacedbythemeansquareerrorofthek-thiteration.TestforChapter8第1题Hopfieldneuralnetworkisakindofneuralnetworkwhichcombinesstoragesystemandbinarysystem.Itnotonlyprovidesamodeltosimulatehumanmemory,butalsoguaranteestheconvergenceto（）.AmaximumBminimumClocalminimumDlocalmaximum第2题Atpresent,researchershavesuccessfullyappliedHopfieldneuralnetworktosolvethetravelingsalesmanproblem(TSP),whichisthemostrepresentativeofoptimizationcombinatorialproblems.第3题In1982,AmericanscientistJohnJosephHopfieldputforwardakindoffeedbackneuralnetwork"Hopfieldneuralnetwork"inhispaperNeuralNetworksandPhysicalSystemswithEmergentCollectiveComputationalAbilities.第4题Undertheexcitationofinputx,DHNNentersadynamicchangeprocess,untilthestateofeachneuronisnolongerchanged,itreachesastablestate.Thisprocessisequivalenttotheprocessofnetworklearningandmemory,andthefinaloutputofthenetworkisthevalueofeachneuroninthestablestate.第5题Theorderinwhichneuronsadjusttheirstatesisnotunique.Itcanbeconsideredthatacertainordercanbespecifiedorselectedrandomly.Theprocessofneuronstateadjustmentincludesthreesituations:from0to1,and1to0andunchanged.TestforChapter9第1题ComparedwithGPU,CPUhashigherprocessingspeed,andhassignificantadvantagesinprocessingrepetitivetasks.第2题Atpresent,DCNNhasbecomeoneofthecorealgorithmsinthefieldofimagerecognition,butitisunstablewhenthereisasmallamountoflearningdata.第3题Inthefieldoftargetdetectionandclassification,thetaskofthelastlayerofneuralnetworkistoclassify.第4题InAlexNet,thereare650000neuronswithmorethan600000parametersdistributedinfiveconvolutionlayersandthreefullyconnectedlayersandSoftmaxlayerswith1000categories.第5题VGGNetiscomposedoftwoparts:theconvolutionlayerandthefullconnectionlayer,whichcanberegardedasthedeepenedversionofAlexNet.TestforChapter10第1题TheessenceoftheoptimizationprocessofDandGistofindthe（）.AmaximumBminimumCminimaxDlocalmaxima第2题Intheartificialneuralnetwork,thequalityofmodelingwilldirectlyaffecttheperformanceofthegenerativemodel,butasmallamountofpriorknowledgeisneededfortheactualcasemodeling.第3题AGANmainlyincludesageneratorGandadiscriminatorD.第4题Becausethegenerativeadversarialnetworkdoesnotneedtodistinguishthelowerboundandapproximateinference,itavoidsthepartitionfunctioncalculationproblemcausedbythetraditionalrepeatedapplicationofMarkovchainlearningmechanism,andimprovesthenetworkefficiency.第5题Fromtheperspectiveofartificialintelligence,GANusesneuralnetworktoguideneuralnetwork,andtheideaisverystrange.TestforChapter11第1题ThecharacteristicofElmanneuralnetworkisthattheoutputofthehiddenlayerisdelayedandstoredbythefeedbacklayer,andthefeedbackisconnectedtotheinputofthehiddenlayer,whichhasthefunctionofinformationstorage.第2题InElmannetwork,thetransferfunctionoffeedbacklayerisnonlinearfunction,andthetransferfunctionofoutputlayeris（）.AlinearfunctionBnonlinearfunctionCcompetitionfunctionDsymbolicfunction第3题

Amongthemanyimprovedboostingalgorithms,themostsuccessfuloneistheAdaBoost(adaptiveboosting)algorithmproposedbyYoavFreundofUniversityofCaliforniaSanDiegoandRobertSchapireofPrincetonUniversityin1996.第4题TheneuronsinthehiddenlayerofElmannetworkadoptthetangentS-typetransferfunction,whiletheoutputlayeradoptsthelineartransferfunction.Ifthereareenoughneuronsinthefeedbacklayer,thecombinationofthesetransferfunctionscanmakeElmanneuralnetworkapproachanyfunctionwitharbitraryprecisioninfinitetime.第5题Elmanneuralnetworkisakindofdynamicrecurrentnetwork,whichcanbedividedintofullfeedbackandpartialfeedback.Inthepartialrecurrentnetwork,thefeedforwardconnectionweightcanbemodified,andthefeedbackconnectioniscomposedofagroupoffeedbackunits,andtheconnectionweightcannotbemodified.TestforChapter12第1题ThelossfunctionofAdaBoostalgorithmis（）.AnonlinearfunctionBlinearfunctionClogarithmicfunctionDexponentialfunction第2题Boostingalgorithmisthegeneralnameofaclassofalgorithms.Theircommongroundistoconstructastrongclassifierbyusingagroupofweakclassifiers.Weakclassifiermainlyreferstotheclassifierwhosepredictionaccuracyisnothighandfarbelowtheidealclassificationeffect.Strongclassifiermainlyreferstotheclassifierwithhighpredictionaccuracy.第3题

Amongthemanyimprovedboostingalgorithms,themostsuccessfuloneistheAdaBoost(adaptiveboosting)algorithmproposedbyYoavFreundofUniversityofCaliforniaSanDiegoandRobertSchapireofPrincetonUniversityin1996.第4题ThemostbasicpropertyofAdaBoostisthatitreducesthetrainingerrorcontinuously