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Bayesian Hypothesis Testing for Sparse Representation
Hadi Zayyani, Massoud Babaie-Zadeh, Christian Jutten
In this paper, we propose a Bayesian Hypothesis Testing Algorithm (BHTA) for sparse representation. It uses the Bayesian framework to determine active atoms in sparse representatio…
On the Achievability of Cramér-Rao Bound In Noisy Compressed Sensing
Rad Niazadeh, Masoud Babaie-Zadeh, Christian Jutten
Recently, it has been proved in Babadi et al. that in noisy compressed sensing, a joint typical estimator can asymptotically achieve the Cramer-Rao lower bound of the problem.To pr…
Bayesian Cramér-Rao Bound for Noisy Non-Blind and Blind Compressed Sensing
Hadi Zayyani, Massoud Babaie-Zadeh, Christian Jutten
In this paper, we address the theoretical limitations in reconstructing sparse signals (in a known complete basis) using compressed sensing framework. We also divide the CS to non-…
Sparse Recovery using Smoothed (SL0): Convergence Analysis
Hosein Mohimani, Massoud Babaie-Zadeh, Irina Gorodnitsky +1
Finding the sparse solution of an underdetermined system of linear equations has many applications, especially, it is used in Compressed Sensing (CS), Sparse Component Analysis (SC…