There are 3 repositories under emd topic.
CEEMDAN_LSTM is a Python project for decomposition-integration forecasting models based on EMD methods and LSTM.
Digital signal analysis library for python. The library includes such methods of the signal analysis, signal processing and signal parameter estimation as ARMA-based techniques; subspace-based techniques; matrix-pencil-based methods; singular-spectrum analysis (SSA); dynamic-mode decomposition (DMD); empirical mode decomposition; variational mode decomposition (EMD); empirical wavelet transform (EWT); Hilbert vibration decomposition (HVD) and many others.
GammaRay: a graphical interface to GSLib and other geomodeling algorithms. *NEW* in Mar, 20th: MCRFSim in batch/unattended mode.
EMD(Empirical Mode decomposition) light weight library, C/C++ language
Simulated annealing lifting for high girth QC-LDPC include ACE/EMD optimization. Make QC-LDPC from protograph (base matrix)
Progressive edge growth PEG for LDPC code and QC-LDPC construction C++, Python, Matlab PEG with ACE and Avoiding Generating Small Cycles
Example of Empirical Mode Decomposition algorithm
Paper reproduction: Instantaneous 3D EEG Signal Analysis Based on Empirical Mode Decomposition and the Hilbert–Huang Transform Applied to Depth of Anaesthesia
Analysis scripts accompanying "Within-cycle instantaneous frequency profiles report oscillatory waveform dynamics" https://doi.org/10.1101/2021.04.12.439547
This python binding for run CUDA kernel code of SFEGO is mimic of Multi-dimensional Ensemble Empirical Mode Decomposition (MEEMD) and this project achieve 10000x faster than MEEMD. Also the result is better than Bi-dimensional Empirical Mode Decomposition. (BEMD)
Diagnóstico de falla de rodamiento utilizando descomposición modal empírica y deep learning
Variational Optimal Transportation
Julia interface for the Python Optimal Transport (POT) library
High-performance parallel GPU implementation of the Multivariate Empirical Mode Decomposition algorithm in CUDA
Holo-Hilbert Spectral Analysis (HHSA) OpenMP version: This program can doing Hilbert–Huang Transform and then doing HHSA.
Rust Optimal Transport solvers
This project is mimic of Multi-dimensional Ensemble Empirical Mode Decomposition (MEEMD) and this project achieve 10000x faster than MEEMD. Also the result is better than Bi-dimensional Empirical Mode Decomposition. (BEMD)
This python binding for run OpenCL kernel code of SFEGO is mimic of Multi-dimensional Ensemble Empirical Mode Decomposition (MEEMD) and this project achieve 10000x faster than MEEMD. Also the result is better than Bi-dimensional Empirical Mode Decomposition. (BEMD)
This Server.py and Client.py can provide send job to multiple GPU Server to run SFEGO in GPU which can make better throughput.
High-performance parallel GPU implementation of the Improved Complete Empirical Mode Decomposition with Adaptive Noise algorithm in CUDA
2016년 엘스비어 논문을 통해 신호 분석에 특화된 EMD, EEMD의 효과를 ARIMA를 통해 확인한다.
Study of time-frequency representations in the presence of heteroscedastic dependent noise