生物神经网络外文翻译文献Word文件下载.docx
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1.Objectives
Asyoureadthesewordsyouareusingacomplexbiologicalneuralnetwork.Youhaveahighlyinterconnectedsetofsome1011neuronstofacilitateyourreading,breathing,motionandthinking.Eachofyourbiologicalneurons,arichassemblyoftissueandchemistry,hasthecomplexity,ifnotthespeed,ofamicroprocessor.Someofyourneuralstructurewaswithyouatbirth.Otherpartshavebeenestablishedbyexperience.
Scientistshaveonlyjustbeguntounderstandhowbiologicalneuralnetworksoperate.Itisgenerallyunderstoodthatallbiologicalneuralfunctions,includingmemory,arestoredintheneuronsandintheconnectionsbetweenthem.Learningisviewedastheestablishmentofnewconnectionsbetweenneuronsorthemodificationofexistingconnections.
Thisleadstothefollowingquestion:
Althoughwehaveonlyarudimentaryunderstandingofbiologicalneuralnetworks,isitpossibletoconstructasmallsetofsimpleartificial“neurons”andperhapstrainthemtoserveausefulfunction?
Theansweris“yes.”Thisbook,then,isaboutartificialneuralnetworks.
Theneuronsthatweconsiderherearenotbiological.Theyareextremelysimpleabstractionsofbiologicalneurons,realizedaselementsinaprogramorperhapsascircuitsmadeofsilicon.Networksoftheseartificialneuronsdonothaveafractionofthepowerofthehumanbrain,buttheycanbetrainedtoperformusefulfunctions.Thisbookisaboutsuchneurons,thenetworksthatcontainthemandtheirtraining.
2.History
Thehistoryofartificialneuralnetworksisfilledwithcolorful,creativeindividualsfrommanydifferentfields,manyofwhomstruggledfordecadestodevelopconceptsthatwenowtakeforgranted.Thishistoryhasbeendocumentedbyvariousauthors.OneparticularlyinterestingbookisNeurocomputing:
FoundationsofResearchbyJohnAndersonandEdwardRosenfeld.Theyhavecollectedandeditedasetofsome43papersofspecialhistoricalinterest.Eachpaperisprecededbyanintroductionthatputsthepaperinhistoricalperspective.
Historiesofsomeofthemainneuralnetworkcontributorsareincludedatthebeginningofvariouschaptersthroughoutthistextandwillnotberepeatedhere.However,itseemsappropriatetogiveabriefoverview,asampleofthemajordevelopments.
Atleasttwoingredientsarenecessaryfortheadvancementofatechnology:
conceptandimplementation.First,onemusthaveaconcept,awayofthinkingaboutatopic,someviewofitthatgivesclaritynottherebefore.Thismayinvolveasimpleidea,oritmaybemorespecificandincludeamathematicaldescription.Toillustratethispoint,considerthehistoryoftheheart.Itwasthoughttobe,atvarioustimes,thecenterofthesoulorasourceofheat.Inthe17thcenturymedicalpractitionersfinallybegantoviewtheheartasapump,andtheydesignedexperimentstostudyitspumpingaction.Theseexperimentsrevolutionizedourviewofthecirculatorysystem.Withoutthepumpconcept,anunderstandingoftheheartwasoutofgrasp.
Conceptsandtheiraccompanyingmathematicsarenotsufficientforatechnologytomatureunlessthereissomewaytoimplementthesystem.Forinstance,themathematicsnecessaryforthereconstructionofimagesfromcomputer-aidedtopography(CAT)scanswasknownmanyyearsbeforetheavailabilityofhigh-speedcomputersandefficientalgorithmsfinallymadeitpracticaltoimplementausefulCATsystem.
Thehistoryofneuralnetworkshasprogressedthroughbothconceptualinnovationsandimplementationdevelopments.Theseadvancements,however,seemtohaveoccurredinfitsandstartsratherthanbysteadyevolution.
Someofthebackgroundworkforthefieldofneuralnetworksoccurredinthelate19thandearly20thcenturies.Thisconsistedprimarilyofinterdisciplinaryworkinphysics,psychologyandneurophysiologybysuchscientistsasHermannvonHelmholtz,ErnstMuchandIvanPavlov.Thisearlyworkemphasizedgeneraltheoriesoflearning,vision,conditioning,etc.,anddidnotincludespecificmathematicalmodelsofneuronoperation.
Themodernviewofneuralnetworksbeganinthe1940swiththeworkofWarrenMcCullochandWalterPitts[McPi43],whoshowedthatnetworksofartificialneuronscould,inprinciple,computeanyarithmeticorlogicalfunction.Theirworkisoftenacknowledgedastheoriginofthe
neuralnetworkfield.
McCullochandPittswerefollowedbyDonaldHebb[Hebb49],whoproposedthatclassicalconditioning(asdiscoveredbyPavlov)ispresentbecauseofthepropertiesofindividualneurons.Heproposedamechanismforlearninginbiologicalneurons.
Thefirstpracticalapplicationofartificialneuralnetworkscameinthelate1950s,withtheinventionoftheperceptionnetworkandassociatedlearningrulebyFrankRosenblatt[Rose58].Rosenblattandhiscolleaguesbuiltaperceptionnetworkanddemonstrateditsabilitytoperformpatternrecognition.Thisearlysuccessgeneratedagreatdealofinterestinneuralnetworkresearch.Unfortunately,itwaslatershownthatthebasicperceptionnetworkcouldsolveonlyalimitedclassofproblems.(SeeChapter4formoreonRosenblattandtheperceptionlearningrule.)
Ataboutthesametime,BernardWidrowandTedHoff[WiHo60]introducedanewlearningalgorithmandusedittotrainadaptivelinearneuralnetworks,whichweresimilarinstructureandcapabilitytoRosenblatt’sperception.TheWidrowHofflearningruleisstillinusetoday.(SeeChapter10formoreonWidrow-Hofflearning.)
Unfortunately,bothRosenblatt'
sandWidrow'
snetworkssufferedfromthesameinherentlimitations,whichwerewidelypublicizedinabookbyMarvinMinskyandSeymourPapert[MiPa69].RosenblattandWidrowwere
awareoftheselimitationsandproposednewnetworksthatwouldovercomethem.However,theywerenotabletosuccessfullymodifytheirlearningalgorithmstotrainthemorecomplexnetworks.
Manypeople,influencedbyMinskyandPapert,believedthatfurtherresearchonneuralnetworkswasadeadend.This,combinedwiththefactthattherewerenopowerfuldigitalcomputersonwhichtoexperiment,
causedmanyresearcherstoleavethefield.Foradecadeneuralnetworkresearchwaslargelysuspended.Someimportantwork,however,didcontinueduringthe1970s.In1972TeuvoKohonen[Koho72]andJamesAnderson[Ande72]independentlyandseparatelydevelopednewneuralnetworksthatcouldactasmemories.StephenGrossberg[Gros76]wasalsoveryactiveduringthisperiodintheinvestigationofself-organizingnetworks.
Interestinneuralnetworkshadfalteredduringthelate1960sbecauseofthelackofnewideasandpowerfulcomputerswithwhichtoexperiment.Duringthe1980sbothoftheseimpedimentswereovercome,andresearch
inneuralnetworksincreaseddramatically.Newpersonalcomputersand
workstations,whichrapidlygrewincapability,becamewidelyavailable.Inaddition,importantnewconceptswereintroduced.
Twonewconceptsweremostresponsiblefortherebirthofneuralnetworks.Thefirstwastheuseofstatisticalmechanicstoexplaintheoperationofacertainclassofrecurrentnetwork,whichcouldbeusedasanassociativememory.ThiswasdescribedinaseminalpaperbyphysicistJohnHopfield[Hopf82].
Thesecondkeydevelopmentofthe1980swasthebackpropagationalgorithmfortrainingmultilayerperceptronnetworks,whichwasdiscoveredindependentlybyseveraldifferentresearchers.ThemostinfluentialpublicationofthebackpropagationalgorithmwasbyDavidRumelhartandJamesMcClelland[RuMc86].ThisalgorithmwastheanswertothecriticismsMinskyandPaperthadmadeinthe1960s.(SeeChapters11and12foradevelopmentofthebackpropagationalgorithm.)
Thesenewdevelopmentsreinvigoratedthefieldofneuralnetworks.Inthelasttenyears,thousandsofpapershavebeenwritten,andneuralnetworkshavefoundmanyapplications.Thefieldisbuzzingwithnewtheoreticalandpracticalwork.Asnotedbelow,itisnotclearwhereallofthiswillleadUS.
Thebriefhistoricalaccountgivenaboveisnotintendedtoidentifyallofthemajorcontributors,butissimplytogivethereadersomefeelforhowknowledgeintheneuralnetworkfieldhasprogressed.Asonemightnote,theprogresshasnotalwaysbeen"
slowbutsure."
Therehavebeenperiodsofdramaticprogressandperiodswhenrelativelylittlehasbeenaccomplished.
Manyoftheadvancesinneuralnetworkshavehadtodowithnewconcepts,suchasinnovativearchitecturesandtraining.Justasimportanthasbeentheavailabilityofpowerfulnewcomputersonwhichtotestthesenewconcepts.
Well,somuchforthehistoryofneuralnetworkstothisdate.Therealquestionis,"
Whatwillhappeninthenexttentotwentyyears?
"
Willneuralnetworkstakeapermanentplaceasamathematical/engineeringtool,orwilltheyfadeawayashavesomanypromisingtechnologies?
Atpresent,theanswerseemstobethatneuralnetworkswillnotonlyhavetheirdaybutwillhaveapermanentplace,notasasolutiontoeveryproblem,butasatooltobeusedinappropriatesituations.Inaddition,rememberthatwestillknowverylittleabouthowthebrainworks.Themostimportantadvancesinneuralnetworksalmostcertainlylieinthefuture.
Althoughitisdifficulttopredictthefuturesuccessofneuralnetworks,thelargenumberandwidevarietyofapplicationsofthisnewtechnologyareveryencouraging.Thenextsectiondescribessomeoftheseapplications.
3.Applications
ArecentnewspaperarticledescribedtheuseofneuralnetworksinliteratureresearchbyAstonUniversity.Itstatedthat"
thenetworkcanbetaughttorecognizeindividualwritingstyles,andtheresearchersusedittocomp