Title:
A-Robust-Algorithm-for-Joint-Sparse
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Description: presents a robust solution for joint sparse
recovery (JSR) under impulsive noise. The unknown measurement
noise is endowed with the Student-t distribution, then a
novel Bayesian probabilistic model is proposed to describe the
JSR problem. To effectively recover the joint row sparse signal,
variational Bayes (VB) method is introduced for Bayesian theory
based JSR algorithms such that it overcomes the intractable
integrations inherent. Simulation results verify that the proposed
algorithm significantly outperforms the existing algorithms under
impulsive noise.
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A Robust Algorithm for Joint Sparse Recovery in Presence of Impulsive Noise.pdf
