60 research outputs found
Simultaneous Sparse Approximation Using an Iterative Method with Adaptive Thresholding
This paper studies the problem of Simultaneous Sparse Approximation (SSA).
This problem arises in many applications which work with multiple signals
maintaining some degree of dependency such as radar and sensor networks. In
this paper, we introduce a new method towards joint recovery of several
independent sparse signals with the same support. We provide an analytical
discussion on the convergence of our method called Simultaneous Iterative
Method with Adaptive Thresholding (SIMAT). Additionally, we compare our method
with other group-sparse reconstruction techniques, i.e., Simultaneous
Orthogonal Matching Pursuit (SOMP), and Block Iterative Method with Adaptive
Thresholding (BIMAT) through numerical experiments. The simulation results
demonstrate that SIMAT outperforms these algorithms in terms of the metrics
Signal to Noise Ratio (SNR) and Success Rate (SR). Moreover, SIMAT is
considerably less complicated than BIMAT, which makes it feasible for practical
applications such as implementation in MIMO radar systems
Recovery of Missing Samples Using Sparse Approximation via a Convex Similarity Measure
In this paper, we study the missing sample recovery problem using methods
based on sparse approximation. In this regard, we investigate the algorithms
used for solving the inverse problem associated with the restoration of missed
samples of image signal. This problem is also known as inpainting in the
context of image processing and for this purpose, we suggest an iterative
sparse recovery algorithm based on constrained -norm minimization with a
new fidelity metric. The proposed metric called Convex SIMilarity (CSIM) index,
is a simplified version of the Structural SIMilarity (SSIM) index, which is
convex and error-sensitive. The optimization problem incorporating this
criterion, is then solved via Alternating Direction Method of Multipliers
(ADMM). Simulation results show the efficiency of the proposed method for
missing sample recovery of 1D patch vectors and inpainting of 2D image signals
- …