Rotating non-uniform and high-dimensional constellations using geodesic flow on lie groups.
David A. KarpukCamilla HollantiPublished in: ICC (2014)
Keyphrases
- lie group
- high dimensional
- parameter space
- euclidean space
- low dimensional
- geodesic distance
- infinite dimensional
- dimensionality reduction
- vector field
- metric space
- similarity search
- riemannian manifolds
- vector space
- data points
- feature space
- nearest neighbor
- input space
- motion analysis
- mean shift
- covariance matrices
- high dimensional data
- linear transformation
- finite dimensional
- manifold learning
- flow field
- visual data
- geometric structure
- higher dimensional
- kernel function
- shortest path