Title:
Subspace-Methods-for-Joint
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Description: We propose subspace-augmented
MUSIC (SA-MUSIC), which improves on MUSIC such that the
support is reliably recovered under such unfavorable conditions.
Combined with a subspace-based greedy algorithm, known as Orthogonal
Subspace Matching Pursuit, which is also proposed and
analyzed in this paper, SA-MUSIC provides a computationally
efficient algorithm with a performance guarantee. The performance
guarantees are given in terms of a version of the restricted
isometry property. In particular, we also present a non-asymptotic
perturbation analysis of the signal subspace estimation step, which
has been missing in the previous studies of MUSIC.
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Subspace Methods for Joint Sparse Recovery.pdf
