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2023-03-12T00:00:00.000Z
On this page
2023-03-12
Combine EMD and LSTM for forecasting
Paper 01
Note: combine EMD and LSTM for time series prediction (with code)
Paper 02
Paper: (delucaavilaFinancialTimeSeries2020, link, DOI, zolib)
Code: avilarenan/xlstmceemdan: XLSTM-CEEMDAN model
Note: similar approach with Paper 02, combine EMD and LSTM for time series prediction (_with code)
Paper 03
Paper: (liuDataDrivenApproachUncertainty2021, link, DOI, zolib)
Iterative Filtering
Note: try use it?
Review EMD in Fault Diagnosis for Rotating Machinery
- (leiReviewEmpiricalMode2013, link, DOI, zolib)
- Compare many EMD variations and implementations
EMD in Fault Diagnosis for Rotating Machinery Examples
- (liuFeatureExtractionRotor2019, link, DOI, zolib)
- Use EEMD, get IMF, calculate SD and CC, use K-means for classification
- Paper: (hasanDeepLearningApproach2019, link, DOI, zolib)
- Code: NahianHasan/Cardiovascular_Disease_Classification_Employing_EMD: Cardiovascular Disease Classification Employing Empirical Mode Decomposition (EMD) of Modified ECG
- Note: employ EMD to ECG classification (with code). Combine first three IMF and then classify using 1D CNN
- (khanSystemDesignEarly2019, link, DOI, zolib)
- Use EMD, get IMF, feature extraction (mean, energy, rms), classify by KNN, using Raspberry Pi
- (delgado-arredondoMethodologyFaultDetection2017, link, DOI, zolib)
- Use EEMD, spectral content using Gabor representation, manual classification
- (xieFaultDiagnosisRotating2017, link, DOI, zolib)
- Get 91 features (80 CNN features (after 2 convolution layers and pooling layers) + 11 time domain and EMD features), classify using Softmax and SVM
- (hanIntelligentFaultDiagnosis2020, link, DOI, zolib)
- EMD, get IMF, feature extraction (time and frequency domain), feature selection (using inner distance), classify using DAE, (read more)
- (shifatEEMDAssistedSupervised2020, link, DOI, zolib)
- EEMD, get IMF, choose the best IMF, get 9 condition indicators (time domain extraction) from the IMF, reduce 9 CI to 2 using PCA, classify using KNN
- IMF selection: similarity based on correlation of IMFs with the original vibration signal
- (leeOptimalIntrinsicMode2019, link, DOI, zolib)
- greedy empirical mode decomposition (GEMD) to select the best IMF. The best IMF has the best accuracy (energy) estimated by the BPNN
[Iterative Filtering](iterative-filtering.model-order-reduction
- (zhangComplementaryEnsembleAdaptive2021, link, DOI, zolib)
- ALIF, modified to CEALIF, get IMF, feature extraction (time and frequency based), Feature Selection-Based Laplacian Score (LS), Genetic Algorithm-Based BPNN as classifier
- (zhaoRollingElementBearing2019, link, DOI, zolib)
- Combined adaptive local iterative filtering decomposition (ALIFD) with Teager–Kaiser energy operator (TKEO)
- (zhangImprovedHigherorderAnalytical2020, link, DOI, zolib)
- Combined adaptive local iterative filtering decomposition (ALIFD) with Higher Order energy operator (HO-EO)
Multi EMD-like Methods
- (fengAdaptiveModeDecomposition2017, link, DOI, zolib)
- Comparison and implementation of many EMD-like methods: EMD/EEMD, Local Mean Decomposition, Intrinsic Time-Scale Decomposition, Local Characteristic Scale Decomposition, Hilbert Vibration Decomposition, Empirical Wavelet Transform, Variational Mode Decomposition, Nonlinear Mode Decomposition, Adaptive Local Iterative Filtering
- (civeraComparativeAnalysisSignal2021, link, DOI, zolib)
- Compare CEEMDAN, HVD, VMD
- (ronkinNumericalAnalysisAdaptive2022, link, DOI, zolib)
- EMD, EWT, VMD
- Also time domain decomposition: MPM, SSA, PCA
- Python for Multi-EMD like methods
- EWT
- ITSD
- VMD
- ALIF
- LMD
Instantaneous Frequency
References
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Last updated on 5/19/2023