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1、4IEEETRANSACTIONSONPATTERNANALYSISANDMACHINEINTELLIGENCE,VOL.22,NO.1,JANUARY2000StatisticalPatternRecognition:AReviewAnilK.Jain,Fellow,IEEE,RobertP.W.Duin,andJianchangMao,SeniorMember,IEEEAbstractÐTheprimarygoalofpatternrecognitionissupervisedorunsupervisedclassification.Among
2、thevariousframeworksinwhichpatternrecognitionhasbeentraditionallyformulated,thestatisticalapproachhasbeenmostintensivelystudiedandusedinpractice.Morerecently,neuralnetworktechniquesandmethodsimportedfromstatisticallearningtheoryhavebeenreceivingincreasingattention.Thedesignofa
3、recognitionsystemrequirescarefulattentiontothefollowingissues:definitionofpatternclasses,sensingenvironment,patternrepresentation,featureextractionandselection,clusteranalysis,classifierdesignandlearning,selectionoftrainingandtestsamples,andperformanceevaluation.Inspiteofalmos
4、t50yearsofresearchanddevelopmentinthisfield,thegeneralproblemofrecognizingcomplexpatternswitharbitraryorientation,location,andscaleremainsunsolved.Newandemergingapplications,suchasdatamining,websearching,retrievalofmultimediadata,facerecognition,andcursivehandwritingrecognitio
5、n,requirerobustandefficientpatternrecognitiontechniques.Theobjectiveofthisreviewpaperistosummarizeandcomparesomeofthewell-knownmethodsusedinvariousstagesofapatternrecognitionsystemandidentifyresearchtopicsandapplicationswhichareattheforefrontofthisexcitingandchallengingfield.I
6、ndexTermsÐStatisticalpatternrecognition,classification,clustering,featureextraction,featureselection,errorestimation,classifiercombination,neuralnetworks.æ1INTRODUCTIONBYthetimetheyarefiveyearsold,mostchildrencandependinsomewayonpatternrecognition...Weneedtorecognizedigitsandl
7、etters.Smallcharacters,largepaymuchmoreexplicitattentiontoteachingpatterncharacters,handwritten,machineprinted,orrotatedÐallrecognition.ºOurgoalhereistointroducepatternrecogni-areeasilyrecognizedbytheyoung.Thecharactersmaybetionasthebestpossiblewayofutilizingavailablesensors,w
8、rittenonaclutteredbackground,oncrumpledpaperorprocessors,andd
