基于核Fisher判别分析和遗传算法的混响环境下钴结壳识别方法（英文）-豆柴文库

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基于核Fisher判别分析和遗传算法的混响环境下钴结壳识别方法（英文）
Title:RecognitionofCobaltStructureShellsinReverberantEnvironmentsusingKernelFisherDiscriminantAnalysisandGeneticAlgorithm
Abstract:
Inrecentyears,thedetectionandrecognitionofobjectsincomplexenvironmentshavebecomeincreasinglyimportantforvariousapplications.Thispaperpresentsanovelmethodforrecognizingcobaltstructureshellsinreverberantenvironments.TheproposedapproachcombinestheKernelFisherDiscriminantAnalysis(KFDA)andtheGeneticAlgorithm(GA)toenhancetheperformanceofobjectrecognitionunderreverberationeffects.Experimentalresultsdemonstratetheeffectivenessoftheproposedmethodinaccuratelyidentifyingcobaltstructureshellsinchallengingenvironments.
1.Introduction:
Objectrecognitioninreverberantenvironmentsposessignificantchallengesduetothepresenceofreflections,echoes,andotherinterferenceeffects.Cobaltstructureshellsarewidelyusedinvariousindustriesandaccuratelyidentifyingthemiscrucialforqualitycontrolpurposes.Thispaperaimstodevelopanefficientandrobustmethodforrecognizingcobaltstructureshellsinthepresenceofreverberation.
2.RelatedWork:
Previousresearchinobjectrecognitionhasexploredvarioustechniquessuchastemplatematching,principalcomponentanalysis,andsupportvectormachines.However,thesemethodsareoftenlimitedintheirabilitytohandlereverberantenvironments.Toaddressthisissue,recentstudieshavefocusedonfeatureextractionalgorithmsandoptimizationtechniques,suchasFisherDiscriminantAnalysisandGeneticAlgorithm.
3.Methodology:
TheproposedmethodcombinesthebenefitsofKernelFisherDiscriminantAnalysis(KFDA)andGeneticAlgorithm(GA).KFDAisemployedtoextractdiscriminativefeaturesfromtheacousticsignalscapturedinthereverberantenvironment.GAisthenusedtooptimizethefeaturesubsetselectiontoenhancetherecognitionperformanceevenfurther.Theproposedmethodconsistsofthefollowingsteps:
3.1DataAcquisition:
Theacousticsignalsfromvariouscobaltstructureshellsarerecordedinareverberantchamberusingamicrophonearray.Multiplemicrophonesensurethatthecollectedsignalscontainavarietyofreflections