A Machine Learning Approach for Classifying Faults in Microgrids using Wavelet Decomposition
Khalaf A, Al Hassan H, Emes A, Akcakaya M, Grainger B. A Machine Learning Approach for Classifying Faults in Microgrids using Wavelet Decomposition. 2019, 00: 1-6. DOI: 10.1109/mlsp.2019.8918774.Peer-Reviewed Original ResearchLinear discriminant analysisWavelet decompositionNaïve Bayesian classifierFault typesClassification problemDifferent fault scenariosClassification performanceVector machineBayesian classifierWavelet coefficientsStatistical featuresFault identificationFault onsetMachineFault scenariosHigh performanceOverall accuracyExperimental resultsThree-phase voltageSignificant featuresMicrogrid architectureTransfer Learning for a Multimodal Hybrid EEG-fTCD Brain–Computer Interface
Dagois E, Khalaf A, Sejdic E, Akcakaya M. Transfer Learning for a Multimodal Hybrid EEG-fTCD Brain–Computer Interface. IEEE Sensors Letters 2019, 3: 1-4. DOI: 10.1109/lsens.2018.2879466.Peer-Reviewed Original ResearchFunctional transcranial Doppler ultrasoundTransfer learningClass-conditional distributionsQuadratic discriminant analysisLinear discriminant analysisCalibration sessionHybrid BCIConditional probabilistic distributionsBetter classification performanceElectrical brain activityBrain-computer interface (BCI) researchMotor imagery tasksTraining dataDifferent classifiersClassification performanceProbabilistic similarityVector machineImagery tasksComputer interfaceBrain activityControl accessDimensionality reductionFinal classificationBCI systemSpecific tasks