In this paper, we propose and study a quadratically constrained `q mini- mization (0 <q< 1) model for finding sparse solutions to a quadratic system.

Sep 30, 2020 · In this paper, we propose a quadratically constrained ℓ q ℓ q (0 < q < 1) minimization model for finding sparse solutions to a quadratic system.

ℓq minimization (0 < q < 1) model for finding sparse solutions to a quadratic system which has wide applications in sparse signal recovery, image processing and.

In this paper, we propose a quadratically constrained ℓ q (0 < q < 1) minimization model for finding sparse solutions to a quadratic system. We prove that ...

In this paper, we propose a quadratically constrained [Formula: see text] (0 < q < 1) minimization model for finding sparse solutions to a quadratic system. We ...

In this paper, we propose a quadratically constrained ℓ q (0 < q < 1) minimization model for finding sparse solutions to a quadratic system. We prove that ...

We study an unconstrained version of the ℓ q minimization for the sparse solution of underdetermined linear systems for 0 < q ≤ 1 .

Sparse Signal Reconstruction via the Approximations of L0 Quasinorm; Sparse Solutions by a Quadratically Constrained Lq (0<q<1) Minimization Model; A Gradient ...

Jul 16, 2014 · Abstract. The paper deals with the problem of finding sparse solutions to systems of polynomial equations possibly perturbed by noise.

An unconstrained version of the lq minimization for the sparse solution of under-determined linear systems for 0 < q ≤ 1 is studied and an iterative ...