GitHub / CardLin / SFEGO_3D_PyCUDA
This code is Spatial Frequency Extraction using Gradient-liked Operator in Three-Dimension (SFEGO_3D) that use gradient and integral to mimic the Multi-dimensional Ensemble Empirical Mode Decomposition (MEEMD) and Three-dimensional Empirical Mode Decomposition (TEMD) in different way. Our code can get 6 Spatial Data (128*128*128) within 1 minutes with modern GPU.
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Stars: 1
Forks: 0
Open issues: 0
License: None
Language: Python
Size: 4.88 KB
Dependencies parsed at: Pending
Created at: almost 3 years ago
Updated at: almost 3 years ago
Pushed at: almost 3 years ago
Last synced at: about 2 years ago
Topics: 3d-emd, cuda, meemd, pycuda, sfego, spatial-frequency, temd