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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 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)
Paper reproduction: Instantaneous 3D EEG Signal Analysis Based on Empirical Mode Decomposition and the Hilbert–Huang Transform Applied to Depth of Anaesthesia
Exemplo de aplicação do método EMD (empirical mode decomposition) apresentado na disciplina "Introdução à Ciência de Dados" pelo professor Rodrigo Mello em 2019, em São Carlos-SP
Comparison of visual odometry transformation reconstruction methods for optimal path estimates and localization using feature detection, description, matching and trajectory generation
Image classification and unsupervised learning using latent space vectors produced by convolutional neural nets together with the original vectors space