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ID:14862028
大小:3.65 MB
页数:148页
时间:2018-07-30
《an introduction to neural networks - kevin gurney》由会员上传分享,免费在线阅读,更多相关内容在学术论文-天天文库。
1、AnintroductiontoneuralnetworksAnintroductiontoneuralnetworksKevinGurneyUniversityofSheffieldLondonandNewYork©KevinGurney1997ThisbookiscopyrightundertheBerneConvention.Noreproductionwithoutpermission.Allrightsreserved.Firstpublishedin1997byUCLPressReprinted1999UCLPressLimited11NewFetterLaneLondo
2、nEC4P4EEUCLPressLimitedisanimprintoftheTaylor&FrancisGroupThiseditionpublishedintheTaylor&Francise-Library,2005.“TopurchaseyourowncopyofthisoranyofTaylor&FrancisorRoutledge’scollectionofthousandsofeBookspleasegotowww.eBookstore.tandf.co.uk.”ThenameofUniversityCollegeLondon(UCL)isaregisteredtrad
3、emarkusedbyUCLPresswiththeconsentoftheowner.BritishLibraryCataloguinginPublicationDataAcataloguerecordforthisbookisavailablefromtheBritishLibrary.ISBN0-203-45151-1Mastere-bookISBNISBN0-203-45874-5(AdobeeReaderFormat)ISBNs:1-85728-673-1(PrintEdition)HB1-85728-503-4(PrintEdition)PBContentsPreface
4、vii1Neuralnetworks—anoverview11.1Whatareneuralnetworks?11.2Whystudyneuralnetworks?31.3Summary41.4Notes42Realandartificialneurons52.1Realneurons:areview52.2Artificialneurons:theTLU82.3Resiliencetonoiseandhardwarefailure102.4Non-binarysignalcommunication112.5Introducingtime122.6Summary142.7Notes1
5、53TLUs,linearseparabilityandvectors163.1GeometricinterpretationofTLUaction163.2Vectors183.3TLUsandlinearseparabilityrevisited223.4Summary233.5Notes244TrainingTLUs:theperceptronrule254.1Trainingnetworks254.2Trainingthethresholdasaweight254.3Adjustingtheweightvector264.4Theperceptron284.5Multiple
6、nodesandlayers294.6Somepracticalmatters314.7Summary334.8Notes335Thedeltarule345.1Findingtheminimumofafunction:gradientdescent34v5.2Gradientdescentonanerror365.3Thedeltarule375.4Watchingthedeltaruleatwork395.5Summary406Multilayernetsandbackpropagation416.1Trainingrulesformultilayernets416.2Theba
7、ckpropagationalgorithm426.3Localversusglobalminima436.4Thestoppingcriterion446.5Speedinguplearning:themomentumterm446.6Morecomplexnets456.7Theactionofwell-trainednets466.8Takingstock506.9Generalizationandovertraining506.10Fosterin
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