High-resolution radar via compressed sensing
IEEE Transactions on Signal Processing
Distributed sampling of signals linked by sparse filtering: theory and applications
IEEE Transactions on Signal Processing
Dictionary identification: sparse matrix-factorization via l1-minimization
IEEE Transactions on Information Theory
Semi-blind most significant tap detection for sparse channel estimation of OFDM systems
IEEE Transactions on Circuits and Systems Part I: Regular Papers
Toeplitz compressed sensing matrices with applications to sparse channel estimation
IEEE Transactions on Information Theory
Matrix Probing and its Conditioning
SIAM Journal on Numerical Analysis
Detection of sparse targets with structurally perturbed echo dictionaries
Digital Signal Processing
| Hi-index | 35.81 |
We consider the problem of recovering a matrix from its action on a known vector in the setting where the matrix can be represented efficiently in a known matrix dictionary. Connections with sparse signal recovery allows for the use of efficient reconstruction techniques such as basis pursuit. Of particular interest is the dictionary of time-frequency shift matrices and its role for channel estimation and identification in communications engineering. We present recovery results for basis pursuit with the time-frequency shift dictionary and various dictionaries of random matrices.