Separating sparse and low-dimensional signal sequences from time-varying undersampled projections of their sums.
Jinchun ZhanNamrata VaswaniIan C. AtkinsonPublished in: ICASSP (2013)
Keyphrases
- low dimensional
- high dimensional
- binary matrices
- compressive sensing
- signal recovery
- random projections
- dimensionality reduction
- signal reconstruction
- sparse data
- signal processing
- compressive sampling
- three dimensional
- binary matrix
- input space
- manifold learning
- dimension reduction
- high dimensional data
- euclidean space
- hidden markov models
- data points
- compressed sensing
- random variables
- sparse representation
- frequency domain
- tomographic reconstruction
- principal component analysis
- discrete tomography
- sparse coding
- linear dimensionality reduction
- linear subspace
- dictionary learning
- graph embedding
- empirical mode decomposition
- multidimensional scaling
- eigenvalue decomposition
- image reconstruction
- linear transform