Recovery of High-Dimensional Sparse Signals via -Minimization
نویسندگان
چکیده
منابع مشابه
Recovery of High-Dimensional Sparse Signals via l1-Minimization
We consider the recovery of high-dimensional sparse signals via l 1 -minimization under mutual incoherence condition, which is shown to be sufficient for sparse signals recovery in the noiseless and noise cases. We study both l 1 -minimization under the l 2 constraint and the Dantzig selector. Using the two l 1 -minimization methods and a technical inequality, some results are obtained. They im...
متن کاملOn recovery of sparse signals via l1 minimization
This article considers constrained l1 minimization methods for the recovery of high dimensional sparse signals in three settings: noiseless, bounded error and Gaussian noise. A unified and elementary treatment is given in these noise settings for two l1 minimization methods: the Dantzig selector and l1 minimization with an l2 constraint. The results of this paper improve the existing results in...
متن کاملStable Recovery of Sparse Signals via $l_p-$Minimization
In this paper, we show that, under the assumption that ‖e‖2 ≤ ǫ, every k−sparse signal x ∈ R can be stably (ǫ 6= 0) or exactly recovered (ǫ = 0) from y = Ax+ e via lp−mnimization with p ∈ (0, p̄], where
متن کاملOn Recovery of Sparse Signals via ℓ1 Minimization
This paper considers constrained minimization methods in a unified framework for the recovery of high-dimensional sparse signals in three settings: noiseless, bounded error, and Gaussian noise. Both minimization with an constraint (Dantzig selector) and minimization under an constraint are considered. The results of this paper improve the existing results in the literature by weakening the cond...
متن کاملRecovery of sparsest signals via ℓq-minimization
In this paper, it is proved that every s-sparse vector x ∈ R can be exactly recovered from the measurement vector z = Ax ∈ R via some `-minimization with 0 < q ≤ 1, as soon as each s-sparse vector x ∈ R is uniquely determined by the measurement z. Moreover it is shown that the exponent q in the `-minimization can be so chosen to be about 0.6796× (1− δ2s(A)), where δ2s(A) is the restricted isome...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Applied Mathematics
سال: 2013
ISSN: 1110-757X,1687-0042
DOI: 10.1155/2013/636094