GitHub - marvande/Non-linear-feature-extraction-of-the-stratoshpere: Dynamical systems such as the climate are highly nonlinear, and despite the fact that the observations are high-dimensional, most of the dynamics is captured by a small number of physically meaningful patterns. In this project we will apply unsupervised dimension reduction techniques for feature extraction, and more specifically, the Nonlinear Laplacian Spectral Analysis (NLSA) [1] approach to extract features from potential vorticity at the level of the stratosphere. NLSA uses the information on the past trajectory of the data and thus allows us to extract representative temporal and spatial patterns. We will compare the results with linear techniques such as Principal Component Analysis.

marvande / Non-linear-feature-extraction-of-the-stratoshpere Public

Notifications You must be signed in to change notification settings
Fork 0
Star 1

Dynamical systems such as the climate are highly nonlinear, and despite the fact that the observations are high-dimensional, most of the dynamics is captured by a small number of physically meaningful patterns. In this project we will apply unsupervised dimension reduction techniques for feature extraction, and more specifically, the Nonlinear L…

1 star 0 forks Branches Tags Activity

Star

Notifications

Branches Tags

Name		Name	Last commit message	Last commit date
Latest commit History 11 Commits
gif		gif
.gitignore		.gitignore
NLSA.ipynb		NLSA.ipynb
NLSA_plots.ipynb		NLSA_plots.ipynb
data_PCA.ipynb		data_PCA.ipynb
functions_takens.py		functions_takens.py
laplacianeigenmaps-PCA-results.ipynb		laplacianeigenmaps-PCA-results.ipynb
laplacianeigenmaps.ipynb		laplacianeigenmaps.ipynb
plots.ipynb		plots.ipynb
takens.py		takens.py