Improved FOCUSS method with two-step reweighted ℓ2 minimization
نویسندگان
چکیده
منابع مشابه
Improved sparse recovery thresholds with two-step reweighted ℓ1 minimization
It is well known that l1 minimization can be used to recover sufficiently sparse unknown signals from compressed linear measurements. In fact, exact thresholds on the sparsity, as a function of the ratio between the system dimensions, so that with high probability almost all sparse signals can be recovered from iid Gaussian measurements, have been computed and are referred to as “weak threshold...
متن کاملImproved FOCUSS method with conjugate gradient (CG) iterations
FOCal Underdetermined System Solver (FOCUSS) is a powerful tool for sparse representation and underdetermined inverse problems. In this paper, we strengthen the FOCUSS method with the following main contributions: (1) we give a more rigorous derivation of the FOCUSS for the sparsity parameter 0 < p < 1 by a nonlinear transform; (2) we develop the CG-FOCUSS by incorporating the conjugate gradien...
متن کاملImproved Iteratively Reweighted Least Squares for Unconstrained Smoothed 퓁q Minimization
In this paper, we first study q minimization and its associated iterative reweighted algorithm for recovering sparse vectors. Unlike most existing work, we focus on unconstrained q minimization, for which we show a few advantages on noisy measurements and/or approximately sparse vectors. Inspired by the results in [Daubechies et al., Comm. Pure Appl. Math., 63 (2010), pp. 1–38] for constrained ...
متن کاملReweighted ℓ1ℓ1 minimization method for stochastic elliptic differential equations
We consider elliptic stochastic partial differential equations (SPDEs) with random coefficients and solve them by expanding the solution using generalized polynomial chaos (gPC). Under some mild conditions on the coefficients, the solution is ‘‘sparse’’ in the random space, i.e., only a small number of gPC basis makes considerable contribution to the solution. To exploit this sparsity, we emplo...
متن کاملIterative Reweighted Singular Value Minimization
In this paper we study general lp regularized unconstrained matrix minimization problems. In particular, we first introduce a class of first-order stationary points for them. And we show that the first-order stationary points introduced in [11] for an lp regularized vector minimization problem are equivalent to those of an lp regularized matrix minimization reformulation. We also establish that...
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: IOP Conference Series: Materials Science and Engineering
سال: 2014
ISSN: 1757-899X
DOI: 10.1088/1757-899x/57/1/012008