人工神經網絡隱層神經元數(shù)的確定.pdf

1、重慶大學碩士學位論文人工神經網絡隱層神經元數(shù)的確定姓名：王立威申請學位級別：碩士專業(yè)：應用數(shù)學指導教師：劉瓊蓀20120526重厭大學碩士學位論文一——莖蘭壟鐾—————————————————————————————————————————————————————————————————————————一一ABSTRACTAn飾cialneuralnetworkisalloptimizationmodelwhichcanabstrac

2、tanddescriptthehumanbrainneuralnetu，orkfrommathematics，Ph3，sicalandbiologicalaspectsBecauseofabilityofpowerfulmapping，itiswidelyusedinvariousapplicationfieldsHoweverduringtheestablisbanentoftheartificialneuralnetworkmode

3、l，oneofthedifficultiesishowtodeterminethenumberofhidden1ayer—neuronsFirstl、。thepapersystematicallyintroducestheartificialneuralnetworkmodel，andsummarizestheneuralnetworkmodelofhiddenlayerneuronnunlberdeterminationmethodi

4、ndomesticandforeignSecondlyitisbrieflydiscussedonsomecreatl、7emethodsandanalyzedthefactorsofthenumbersofhiddenlayerneuronsThirdly，byintroducingthepolynomialandthethoughtofmatrixpseudoinverse：thepaperwoulddiscussthenumber

5、ofhiddenlayerneuronswhichareneededwhentheneuralnetworkmodelsareestablishedinonedimensionandmulti—dimensionalspacerespectivelyInonedimensionspace，thepaperwouldusethepowerfunctionashiddenlayerneuronactivationfuncti。nandcom

6、binewiththethoughtofmatrixinversetofirstlydetenninetheneuronsoftheoutputweightsandestablishthepolynomialneuralnetworkmodelsFinally，Throughtheintroductionofintervalbinarysearchmethod，thebestnumberofthehiddenla3，erneuronsw

7、ouldbedeterminedInthemulti—dimensionalspacethepaperusesthespecificwa)7todeterminetheinputweightssothatthepurposeofdimensionconversionwou]dberealized，andusestheSfunctionaStheneuronactivationfunctionjcombineswiththethought

8、ofmatrixinverseandfirstlydeterminestheneuronsoftheoutputweights，thepoly7nomialneuralnetworkmodelwouldbeestablishedatIastAndaccordingtothedimensionofthespaceofpolynomialsthenumberofthehiddenlayerneuronsoftheneuralnetworkm