Benchmarking sparse system identification with low-dimensional chaos.
Alan A. KaptanogluLanyue ZhangZachary G. NicolaouUrban FaselSteven L. BruntonPublished in: CoRR (2023)
Keyphrases
- low dimensional
- high dimensional
- high dimensional data
- sparse data
- random projections
- dimensionality reduction
- data points
- manifold learning
- input output
- feature space
- input space
- eigenvalue decomposition
- high dimension
- dimension reduction
- similarity search
- neural network
- compressive sensing
- embedding space
- principal component analysis
- nearest neighbor
- subspace learning
- vector space
- multidimensional scaling
- image processing
- sparse coding
- underlying manifold
- chaos theory
- nonlinear dimensionality reduction
- recurrent neural networks
- particle swarm optimization
- training set
- graph embedding
- sparse matrix
- data sets
- sparse representation