1.1k citations · 1.3k across the 19 of their papers we have counts for
19 papers
Successive Concave Sparsity Approximation for Compressed Sensing
Mohammadreza Malek-Mohammadi, Ali Koochakzadeh, Massoud Babaie-Zadeh +2
In this paper, based on a successively accuracy-increasing approximation of the norm, we propose a new algorithm for recovery of sparse vectors from underdetermined measur…
Iterative Concave Rank Approximation for Recovering Low-Rank Matrices
Mohammadreza Malek-Mohammadi, Massoud Babaie-Zadeh, Mikael Skoglund
In this paper, we propose a new algorithm for recovery of low-rank matrices from compressed linear measurements. The underlying idea of this algorithm is to closely approximate the…
Upper Bounds on the Error of Sparse Vector and Low-Rank Matrix Recovery
Mohammadreza Malek-Mohammadi, Cristian R. Rojas, Magnus Jansson +1
Suppose that a solution to an underdetermined linear system is given. is approximately sparse…
Performance Guarantees for Schatten- Quasi-Norm Minimization in Recovery of Low-Rank Matrices
Mohammadreza Malek-Mohammadi, Massoud Babaie-Zadeh, Mikael Skoglund
We address some theoretical guarantees for Schatten- quasi-norm minimization () in recovering low-rank matrices from compressed linear measurements. Firstly, using…
DOA Estimation in Partially Correlated Noise Using Low-Rank/Sparse Matrix Decomposition
Mohammadreza Malek-Mohammadi, Magnus Jansson, Arash Owrang +2
We consider the problem of direction-of-arrival (DOA) estimation in unknown partially correlated noise environments where the noise covariance matrix is sparse. A sparse noise cova…
Sparse Channel Estimation by Factor Graphs
Rad Niazadeh, Masoud Babaie-Zadeh, Christian Jutten
The problem of estimating a sparse channel, i.e. a channel with a few non-zero taps, appears in various areas of communications. Recently, we have developed an algorithm based on i…