简介：Theanalysisoftheradiatednoiseofvesselsgiveninthispapershowssomestrongsuperposedlinecomponentsinlowfrequencyspeetrumbelow100Hzoccurringatdiscretefrequencieswhichcorrespondwiththerotationspeedofpropellershaft,orpropellerbladefrequency,ortheirharmonicfre-quencies.sincethelinecomponentsreflectpropeller＇workingcharacteristics,thepropller＇sfeaturescanbeextracteddirectlyfromlow-frequencylinecom-ponentsinadditiontodemodulatedlinecomponent.Sotherearetwowaystoextractthefeatures,oneisdirectway,theotherisdemodulationway.Detec-tionperformanceofthelinecomponentinbackground-noiseisdiscussedinthispaper.ThesignallevelisdefinedasthedifrerencebetweenthePDF＇s(ProbabilityDensityFunction)meanofthepeakofthelinecomponentandPDF＇smeanorthebackground-noise.Indircetwaythesignallevelofthelinecomponentisproportionaltothesignalnoiseratio(S/N).Indemodulationwaythesignallevelofdemodulatedlinecomponent

简介：Usingtheextremedifferenceofself-similarityandkurtosisatlargelevelscaleofwavelettransformapproximationbetweenthePTFM(PulseTrainsofFrequencyModulated)signalsanditsreverberation,afeature-basedmatchedfiltermethodusingtheclassify-before-detectparagriamisproposedtoimprovethedetectionperformanceinreverberationandmultipathenvironments.Processingthedataoflake-trailsshowedthattheprocessinggainoftheproposedmethodisbiggerthanthatofmatchedfilterabout10dB.Inmultipathenvironments,detectionperformanceofmatchedfilterbecomebadlypoorer,whilethatoftheproposedmethodisimprovedbetter.Itshowsthatthemethodismuchmorerobustwiththeeffectofmultipath.

简介：Soundsourcerecognitionisapartofenvironmentalsoundrecognition,whichisoneofthemostimportantresearchareasinpatternrecognition.Impactsoundscarrymuchphysicalinformationassociatedwiththesoundsources,whichmakesimpactsoundbasedsoundsourcerecognitionanimportantapproachtoimproverecognitionperformance.Inthisstudy,theimpactsoundcontinuumsynthesizedwithaball-platecollisionmodelisusedformaterialrecognitionoftheimpactedplates.Thebasisfunctionlearningmethodandtime-frequencyrepresentationmethods,includingtheshorttimeFouriertransformandthewaveletpackettransform,areappliedintoclassificationandtherecognitionresultsarecompared.TheresultshowsthatthefeaturesobtainedbyusingthebasisfunctionlearningperformbetterformaterialclassificationoftheimpactedplatesthanthatbyusingtheshorttimeFouriertransformandthewaveletpackettransform.Thisdemonstratesthehighefficiencyandsuperiorityofthismethodinmaterialrecognitionofsoundsources.

简介：到识别问题的轮船噪音解调光谱泛音氏族特征和相应应用的结构法律被理论推导和样品分析学习。以便认出推进器片数字，轮船推进器成穴噪音模型根据五个假设被建立。进一步，结构法律的数学表达式被模型推出。并且推进器片数字的类空格算术地被分析。结果能被使用作为专家知识指向识别。最后，实验样品的解调光谱泛音氏族被使用小浪包获得。结构法律被实验样品的统计分析验证。实验样品的统计平均结果与理论结构法律一致很好，这被显示出，并且78.6%样品基本上与理论结构法律一致。

简介：InordertoimprovetheperformanceofdeceptiondetectionbasedonChinesespeechsignals,amethodofsparsedecompositiononspectralfeatureisproposed.First,thewaveletpackettransformisappliedtodividethespeechsignalintomultiplesub-bands.Bandcepstralfeaturesofwaveletpacketsareobtainedbyoperatingthediscretecosinetransformonlogarithmicenergyofeachsub-band.ThecepstralfeatureisgeneratedbycombingMelFrequencyCepstralCoefficientandWaveletPacketBandCepstralCoefficient.Second,K-singularvaluedecompositionalgorithmisemployedtoachievethetrainingofanover-completemixturedictionarybasedonboththetruthanddeceptivefeaturesets,andanorthogonalmatchingpursuitalgorithmisusedforsparsecodingaccordingtothemixturedictionarytogetsparsefeature.Finally,recognitionexperimentsareperformedwithvariousclassifiedmodules.Experimentalresultsshowthatthesparsedecompositionmethodhasbetterperformancecompariedwithconventionaldimensionreducedmethods.Therecognitionaccuracyofthemethodproposedinthispaperis78.34%,whichishigherthanmethodsusingotherfeatures,improvingtherecognitionabilityofdeceptiondetectionsystemsignificantly.

简介：Aspeakermodelcalledcompletefeaturecorpus(CFC)anaanevaluationofmutualinformation(MIE)areproposedfortext-independentspeakeridentification.TheCFCmodelrepresentsthespeechandpronunciationcharacteristicsofspeakerbyafeaturevectorcorpuswhichwastrainedfromsometypicalspeechsamples.Ithiresmulti-stepmini-maxsearchmatchingschemeforMIEalgorithmtoevaluatethesimilarityofspeechfeaturesbetweeninputspeechandthemodelsilldistanceandinformationspace.Maximummutualinformation(MMI)decisioncriterionisusedtodecidetheidentityofspeaker.ExperimentsonperformanceanalysiswithcomparisontoGMMmethodshowthatproposedmodelandevaluationalgorithmarequiteeffectiveandpresentedahigherperformancethanordinaryGMMmethod.

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简介：Thesafetyofrailisveryimportantforthedevelopmentofhighspeedrailway,anditisnecessarytoinvestigatethefeaturesofinnercracksinrail.InordertoobtainthefeaturesofAcousticEmission(AE)sourcesofinnercracksinrail,AEsourceswithdifferenttypes,depthsandpropagationdistancesareexaminedforcrackinrail.Thefiniteelementmethodisutilizedtomodeltherailwithcracksandtheresultsofexperimentdemonstratetheeffectivenessofthismodel.WavelettransformandRayleigh-LambequationsareutilizedtoextractthefeaturesofcrackAEsources.TheresultsillustratethattheintensityratioamongAEmodescanidentifytheAEsourcetypesandtheAEsourceswithdifferentfrequenciesinrail.ThereareuniformAEmodefeaturesexistingintheAEsignalsfromAEsourcesinrailweb,howeverAEsignalsfromAEsourcesinrailheadandrailbasehavethecomplexandunstableAEmodes.DifferentAEsourcetypeshavethedifferentpropagationfeaturesinrail.ItishelpfultounderstandtherailcracksanddetecttherailcracksbasedontheAEtechnique.

简介：有Doppler超声技术的传播emboli的非侵略的察觉具有在临床的applications.In顺序的活跃意义消除探针或病人的运动带的人工制品的缺点并且精确地检测emboli，相关特征参数从信号波形的Dopplersignals.The奇特的小浪变换的二个角度被提取基于它的小浪由易到难的试题程序被分析；然后横向、纵的参数被提取到represen

简介：Foraccuracyandrapidityofaudioeventdetectioninthemass-dataaudioprocessingtasks,agenericmethodofrapidlyrecognizingaudioeventbasedon2D-HaaracousticsuperfeaturevectorandAdaBoostisproposed.Firstly,itcombinescertainnumberofcontinuousaudioframestobean'acousticfeatureimage',secondly,usesAdaBoost.MHorfastRandomAdaBoostfeatureselectionalgorithmtoselecthighrepresentative2D-Haarpatterncombinationstoconstructsuperfeaturevectors;thirdly,analyzesthecommonalityanddifferencesbetweensubcategories,thenextractscommonfeaturesandreducesdifferentfeaturestoobtainagenericaudioeventtemplate,whichcansupporttheaccurateidentificationofmultiplesub-classesanddetectandlocatethespecificaudioeventfromtheaudiostreamaccurately.Experimentalresultsshowthattheuseof2D-Haaracousticfeaturesupervectorcanmakerecognitionaccuracy5%higherthanonesthatMFCC,PLP,LPCCandothertraditionalacousticfeaturesyielded,andcanmakethetrainingprocessing7-20timesfasterandtherecognitionprocessing5-10timesfaster,itcanevenachieveanaverageprecisionof93.38%,anaveragerecallof95.03%undertheoptimalparameterconfigurationfoundbygridmethod.Aboveall,itcanprovideanaccurateandfastmass-dataprocessingmethodforaudioeventdetection.

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