A novel block Bayesian hypothesis testing algorithm (BBHTA) is presented for reconstructing block-sparse signals with unknown block structures. The BBHTA detects and recovers the supports and then estimates the amplitudes of block sparse signal. The support detection and recovery are performed by a Bayesian hypothesis testing. Using the detected and reconstructed supports, the nonzero amplitudes are then estimated by linear minimum mean-square error estimation. Numerical experiments demonstrate the effectiveness of BBHTA
We consider the problem of recovering block sparse signals with unknown block partition and propose ...
This thesis builds upon the problem of sparse signal recovery from the Bayesian standpoint. The adva...
We consider the problem of recovering block-sparse signals whose structures are unknown \emph{a prio...
In this paper we study the recovery of block sparse signals and ex-tend conventional approaches in t...
This paper presents a novel iterative Bayesian algorithm, Block Iterative Bayesian Algorithm (Block-...
This paper presents a novel Block Iterative Bayesian Algorithm (Block-IBA) for reconstructing block-...
In this paper, we introduce a new support recovery algorithm from noisy measurements called Bayesian...
Abstract—In this paper, we propose a sparse recovery al-gorithm called detection-directed (DD) spars...
Solving the inverse problem of compressive sensing in the context of single measurement vector (SMV)...
Abstract One of the main challenges in block-sparse signal recovery, as encountered in, e.g., multi...
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In this paper, we develop a low-complexity message passing algorithm for joint support and signal re...
Abstract Block-sparse signal recovery without knowledge of block sizes and boundaries, such as thos...
Nowadays, high-speed sampling and transmission is a foremost challenge of radar system. In order to ...
Abstract—In this paper, we develop a new sparse Bayesian learning method for recovery of block-spars...
We consider the problem of recovering block sparse signals with unknown block partition and propose ...
This thesis builds upon the problem of sparse signal recovery from the Bayesian standpoint. The adva...
We consider the problem of recovering block-sparse signals whose structures are unknown \emph{a prio...
In this paper we study the recovery of block sparse signals and ex-tend conventional approaches in t...
This paper presents a novel iterative Bayesian algorithm, Block Iterative Bayesian Algorithm (Block-...
This paper presents a novel Block Iterative Bayesian Algorithm (Block-IBA) for reconstructing block-...
In this paper, we introduce a new support recovery algorithm from noisy measurements called Bayesian...
Abstract—In this paper, we propose a sparse recovery al-gorithm called detection-directed (DD) spars...
Solving the inverse problem of compressive sensing in the context of single measurement vector (SMV)...
Abstract One of the main challenges in block-sparse signal recovery, as encountered in, e.g., multi...
Abstract We consider the problem of recovering an image using block compressed sensing (BCS). Tradi...
In this paper, we develop a low-complexity message passing algorithm for joint support and signal re...
Abstract Block-sparse signal recovery without knowledge of block sizes and boundaries, such as thos...
Nowadays, high-speed sampling and transmission is a foremost challenge of radar system. In order to ...
Abstract—In this paper, we develop a new sparse Bayesian learning method for recovery of block-spars...
We consider the problem of recovering block sparse signals with unknown block partition and propose ...
This thesis builds upon the problem of sparse signal recovery from the Bayesian standpoint. The adva...
We consider the problem of recovering block-sparse signals whose structures are unknown \emph{a prio...