Phase Transition in Mixed ℓ2/ℓ1-norm Minimization for Block-Sparse Compressed Sensing

Toshiyuki Tanaka
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Abstract

We have evaluated, via the replica method, phase transition thresholds for the mixed ℓ2/ℓ1-norm minimization applied to block-sparse compressed sensing with randomly generated measurement matrices. Our analysis takes into account that the matrix elements may be of non-zero mean, and shows that the phase transition threshold for the mixed ℓ2/ℓ1-norm minimization improves when the matrix elements have non-zero mean and the distribution of non-zero blocks of the target vector to be estimated has a certain imbalance.
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块稀疏压缩感知中混合l2 / l1范数最小化的相变
我们通过复制方法评估了用于随机生成测量矩阵的块稀疏压缩感知的混合2/ 1范数最小化的相变阈值。我们的分析考虑到矩阵元素可能具有非零均值,并表明当矩阵元素具有非零均值且待估计目标向量的非零块分布具有一定的不平衡性时,混合最小化的相变阈值提高。
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