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BuildingAIapplicationsforSignalsandTime-SeriesDataEshaShah,FrancisTiong,MachineMachineLearningandDeeplearninghavegrownrapidlyoverthelastdecade22DEEPDEEPNeuralnetworks,GANs,MACHINESupervisedandUnsupervisedStatisticalARTIFICIALARTIFICIALARTIFICIALMACHINESupervisedandUnsupervisedStatisticalDEEPNeuralnetworks,GANs,4UseofAIinsignalprocessingapplicationsisgrowing4ModulationModulationClassificationofRF44DefinedRadio)DefinedRadio)DefinedRadio)DefinedRadio)DefinedRadio)DefinedRadio)DefinedRadio)DefinedRadio)DefinedRadio)DefinedRadio)DefinedRadio)DefinedRadio)AI-drivenAI-drivensystemLABE欢LABE欢 AI-drivenAI-drivensystem55generateddataHumanDatacleansingandDatageneratedgenerateddataHumanDatacleansingandDataacceleratedtrainingModeldesignandAIgenerateddataHumangenerateddataHumanDatacleansingandDataacceleratedtrainingModeldesignandAIEdge,cloud,EnterpriseEmbeddedacceleratedacceleratedtrainingModeldesignandAIgenerateddataHumanDatacleansingandDataEdge,cloud,EnterpriseEmbeddedPreparingandlabellingDataDataDataDatacleansingandHumanHumanDatacleansingandPreparingandDatacleansingandDataDataQ.HowtolabelcollectedHumanHumanPreparingandlabellingDataDataQ.HowtolabelcollectedHumanDataHumanDatacleansingandLabelingLabelingSignalswithSignalLabelerPAGE7PAGE7GenerateGenerateSyntheticDataforvariousapplicationsin88SimulateSimulatedatausingSimulinkSimulatedataSimulatedatausingSimulinkGeneratewirelessSimulatedataSimulatedatausingSimulinkGeneratewirelessGenerateGenerateRadarSimulatedataSimulatedatausingSimulinkGeneratewirelessGenerateGenerateRadarGenerateandAugmentAudioGenerationGenerationofwirelesscommunicationwaveformswith99Modulatedigitalbasebandsignalsusingbuilt-inBPSK,QPSK,8PSK,FM,DSB-AM,SSB-AM,Modulatedigitalbasebandsignalsusingbuilt-inBPSK,QPSK,8PSK,FM,DSB-AM,SSB-AM,EasilyaccountforvariousRF/Hardwareimpairments(Frequency/PhaseOffsetsetc.ChannelImpairments(MultipathFadingModulatedigitalbasebandsignalsusingbuilt-inBPSK,QPSK,8PSK,FM,DSB-AM,SSB-AM,EasilyaccountforvariousRF/Hardwareimpairments(Frequency/PhaseOffsetsetc.ChannelImpairments(MultipathFadingGenerateDatasetsforDeep5000framesgeneratedforeachmodulation80%data–Training;10%data–Validation;10%data-FeatureDataDataDataDatacleansingandHumanHumanFeatureDataDataDatacleansingandQ.CanIDatacleansingandHumanHumanFeatureDataDataDatacleansingandQ.CanIDatacleansingandHumanHumanUseUseofrawdataforAILABE欢LABE欢 UseUseofrawdataforAIIQ

IQIQ

IQ

ChallengeswithRawNeedNeedformoreNeedforspecializedmodelsFeatureFeatureextractionwithsignalprocessing BuildingtheAIAIAIModelModeldesignacceleratedtrainingBuildingtheAIModeldesignModeldesignAIacceleratedtrainingBuildingtheAIModeldesignModeldesignAIacceleratedtrainingIfIdonothaveacceleratedtrainingIfIdonothavedomainIfIneedaneasilyinterpretableStartStartbyusingpublishedliteratureandMATLABUnderstandingUnderstandingtradeoffsformodelDataDataTimeDataDataSignalProcessing/DomainThereTherearethreewaystobuildAImodelsinWritingWriting

InteractivelyDesignModels Writing

InteractivelyDesignModels

UseTransferforDeepIterateIteratetofindthebestmodelwithExperimentManager FindoptimaltrainingFindoptimaltrainingoptionsFindoptimaltrainingoptionsFindoptimaltrainingoptionsComparetheresultsofusingdifferentdatasetsFindoptimaltrainingoptionsComparetheresultsofusingdifferentFindoptimaltrainingoptionsComparetheresultsofusingdifferentdatasetsComparetheresultsofusingdifferentmodelsSelectingSelectingtheRightModel:UnderstandingSignalProcessingSignalProcessingDomainDataDataDataDataContinuousContinuousWaveletTransformisusedtoextracttheTime-FrequencymapsOnelineofcodeforgeneratingwavelettime-frequencyvisualizationinMATLAB.Worksforany>>Onelineofcodeforgeneratingwavelettime-frequencyvisualizationinMATLAB.Worksforany>>LocalizessharptransientsandslowlyvaryingoscillationssimultaneouslyOnelineofcodeforgeneratingwavelettime-frequencyvisualizationinMATLAB.Worksforany>>LocalizessharptransientsandslowlyvaryingoscillationssimultaneouslyWorkswithcomplexUsingUsingtime-frequencymapsasinputstoapretrained TransferTransferLearningwithDeepNetworkDesignerTrainTrainandTestDeep[iiTrainingPro,gress(05-Mar-

TrainiingProgress,(05-Mar-

T「ainingite「alion2of12.260 lr.iining~65芒

Start 05-Mar-202112Elapsed 19l@inig 1lteraHonspe「 Maxim11111仆e「 F『 50ite「oc oc lte「 s ss

otherI-la『dwareresource SingleGPULearning「ateschedule IILearn—iraining(smooth的 --e--|Epoc|

iraining(smoothed)lie「 -嘈 八TL八TLABE欢 TestTestDeep||邻仆sConfusio:n庙廿仅1['叩它ra||邻仆s凸凸八TL八TLABE欢 TestingTestingnetworkwithconnected AI-assistedAI-assistedsystemgenerateddataHumangenerateddataHumanDatacleansingandDataacceleratedModeldesignandAIEdge,cloud,EnterpriseEmbeddedDataDataAIDatacleansingandModeldesignandHumanacceleratedgenerateddataEdge,cloud,EnterpriseEmbeddedDeepDeepLearningcanbeusedineachstepoftheAI

Labeling

LabelingassistanceclassifySound(YAMNet),GoogLeNet,

Labeling SyntheticDataclassifySound(YAMNet),GoogLeNet,

Labeling SyntheticDataclassifySound(YAMNet),GoogLeNet,

GenerativeAdversarialNetworksDeepDeepLearningcanbeusedineachstepoftheAIFeatureFeatureFeaturevggFeatures,FeaturevggFeatures,

DifferentiableSignalFeaturevggFeatures,

DifferentiableSignalFeaturevggFeatures,

DifferentiableSignaldlstft(DifferentiableAI-drivenAI-drivensystemgenerateddataHumangenerateddataHumanDatacleansingandDataacceleratedModeldesignandAIEmbeddedEnterpriseEdge,cloud,DeployDeploytoanyprocessorwithbest-in-classPreprocessing,FeatureExtraction,AIModel Preprocessing,FeatureExtraction,AIModel Preprocessing,Fea

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