Low cost sparse subspace tracking algorithms.
Nacerredine LassamiAbdeldjalil Aïssa-El-BeyKarim Abed-MeraimPublished in: Signal Process. (2020)
Keyphrases
- low cost
- high dimensional
- regularized regression
- low dimensional
- low rank representation
- sparse data
- sparse representation
- digital camera
- subspace learning
- low power
- feature space
- high dimensional data
- real time
- basis vectors
- principal component analysis
- sparse coding
- dimensionality reduction
- rank minimization
- subspace clustering
- feature extraction
- orthogonal matching pursuit
- eigendecomposition
- linear subspace
- highly efficient
- data acquisition
- principal components analysis
- semi supervised
- lower dimensional
- power consumption
- input data