Sparse Recovery of Sign Vectors under Uncertain Sensing Matrices.
Hang ZhangAfshin AbdiFaramarz FekriPublished in: ITW (2018)
Keyphrases
- sparse matrix
- coefficient matrix
- covariance matrices
- singular vectors
- singular values
- singular value decomposition
- matrix representation
- decision making
- high dimensional
- sensor networks
- compressive sensing
- symmetric matrices
- low rank approximation
- vector space
- data sets
- sparse data
- sparse representation
- binary matrices
- sensor fusion
- feature vectors
- low rank matrices
- rows and columns
- recovery algorithm
- incomplete information
- low rank matrix
- positive definite
- uncertain information
- signal recovery
- independent component analysis
- real time
- neural network
- feature selection
- tensor factorization
- basis vectors
- least squares
- possibility theory
- linear systems
- random projections
- low rank
- sparse coding