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Since that reweighted minimization can enhance the sparsity and the chaotic iterative algorithm can reduce the computational complexity of the generalized inverse A †, we iteratively solve the following weighted ℓ 1 minimization problem: min u { ∥ u ∥ ω : A u = f }. (4.3).
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This shows that similar as the standard sparse signal recovery, when compared with the convex minimization method, the non-convex minimization method can enhance performance of block-sparse signal recovery.
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