We study the multiple-sets split feasibility problem that requires to find a point closest to a family of closed convex sets in one space such that its image under a linear transformation will be closest to another family of closed convex sets in the image space. By casting the problem into an equivalent problem in a suitable product space we are able to present a simultaneous subgradients projections algo-rithm that generates convergent sequences of iterates in the feasible case. We further derive and analyze a perturbed projection method for the multiple-sets split feasibility problem and, additionally, furnish alternative proofs to two known results. 1
Abstract. Problems in signal detection and image recovery can sometimes be formulated as a convex fe...
Due to their extraordinary utility and broad applicability in many areas of classical mathematics an...
AbstractLet C and Q be nonempty closed convex sets in Rn and Rm, respectively, and A an m by n real ...
AbstractWe study the multiple-sets split feasibility problem that requires to find a point closest t...
This paper deals with the split feasibility problem that requires to find a point closest to a close...
The multiple-set split feasibility problem (MSSFP), as a generalization of the split feasibility pro...
summary:In this paper, we present a simultaneous subgradient algorithm for solving the multiple-sets...
AbstractA unified framework is presented for studying the convergence of projection methods for find...
AbstractAn iterative method to solve the convex feasibility problem for a finite family of convex se...
Abstract The convex feasibility problem (CFP) is at the core of the modeling of many problems in var...
We study some methods of subgradient projections for solving a convex feasibility problem with gener...
In this paper we consider a projection method for convex feasibility problem that is known to conver...
In this paper, we construct an iterative scheme and prove strong convergence theorem of the sequence...
In this paper, we first study in a Hilbertian framework the weak convergence of a general Gradient P...
Our purpose in this paper is to introduce an iterative scheme for solving multiple-set split feasibl...
Abstract. Problems in signal detection and image recovery can sometimes be formulated as a convex fe...
Due to their extraordinary utility and broad applicability in many areas of classical mathematics an...
AbstractLet C and Q be nonempty closed convex sets in Rn and Rm, respectively, and A an m by n real ...
AbstractWe study the multiple-sets split feasibility problem that requires to find a point closest t...
This paper deals with the split feasibility problem that requires to find a point closest to a close...
The multiple-set split feasibility problem (MSSFP), as a generalization of the split feasibility pro...
summary:In this paper, we present a simultaneous subgradient algorithm for solving the multiple-sets...
AbstractA unified framework is presented for studying the convergence of projection methods for find...
AbstractAn iterative method to solve the convex feasibility problem for a finite family of convex se...
Abstract The convex feasibility problem (CFP) is at the core of the modeling of many problems in var...
We study some methods of subgradient projections for solving a convex feasibility problem with gener...
In this paper we consider a projection method for convex feasibility problem that is known to conver...
In this paper, we construct an iterative scheme and prove strong convergence theorem of the sequence...
In this paper, we first study in a Hilbertian framework the weak convergence of a general Gradient P...
Our purpose in this paper is to introduce an iterative scheme for solving multiple-set split feasibl...
Abstract. Problems in signal detection and image recovery can sometimes be formulated as a convex fe...
Due to their extraordinary utility and broad applicability in many areas of classical mathematics an...
AbstractLet C and Q be nonempty closed convex sets in Rn and Rm, respectively, and A an m by n real ...