Practical ReProCS for separating sparse and low-dimensional signal sequences from their sum - Part 1.
Han GuoChenlu QiuNamrata VaswaniPublished in: ICASSP (2014)
Keyphrases
- low dimensional
- high dimensional
- signal recovery
- compressive sensing
- dimensionality reduction
- manifold learning
- signal processing
- signal reconstruction
- frequency domain
- high dimensional data
- random projections
- input space
- sparse data
- high frequency
- sparse representation
- principal component analysis
- objective function
- feature extraction
- real world
- data points
- hidden markov models
- sequential patterns
- dimension reduction
- graph embedding
- compressive sampling
- euclidean space
- sparse coding
- similarity search
- feature space
- pattern recognition
- multiscale
- machine learning