AbstractWe 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 algorithm 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
We consider simple projection methods for solving convex feasibility problems. Both successive and s...
Given closed convex sets $C_i$, $i=1,\ldots,\ell$, and some nonzero linear maps $A_i$, $i = 1,\ldots...
The multiple-sets split feasibility problem (MSFP) captures various applications arising in many are...
AbstractWe study the multiple-sets split feasibility problem that requires to find a point closest t...
We study the multiple-sets split feasibility problem that requires to find a point closest to a fami...
summary:In this paper, we present a simultaneous subgradient algorithm for solving the multiple-sets...
The multiple-set split feasibility problem (MSSFP), as a generalization of the split feasibility pro...
This paper deals with the split feasibility problem that requires to find a point closest to a close...
AbstractA unified framework is presented for studying the convergence of projection methods for find...
Abstract. Problems in signal detection and image recovery can sometimes be formulated as a convex fe...
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...
In this paper, we study the cyclic algorithm for the split common fixed point problem (SCFPP) and mu...
AbstractThe purpose of this paper is to introduce and analyze an extragradient method with regulariz...
AbstractLet C and Q be nonempty closed convex sets in Rn and Rm, respectively, and A an m by n real ...
We consider simple projection methods for solving convex feasibility problems. Both successive and s...
Given closed convex sets $C_i$, $i=1,\ldots,\ell$, and some nonzero linear maps $A_i$, $i = 1,\ldots...
The multiple-sets split feasibility problem (MSFP) captures various applications arising in many are...
AbstractWe study the multiple-sets split feasibility problem that requires to find a point closest t...
We study the multiple-sets split feasibility problem that requires to find a point closest to a fami...
summary:In this paper, we present a simultaneous subgradient algorithm for solving the multiple-sets...
The multiple-set split feasibility problem (MSSFP), as a generalization of the split feasibility pro...
This paper deals with the split feasibility problem that requires to find a point closest to a close...
AbstractA unified framework is presented for studying the convergence of projection methods for find...
Abstract. Problems in signal detection and image recovery can sometimes be formulated as a convex fe...
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...
In this paper, we study the cyclic algorithm for the split common fixed point problem (SCFPP) and mu...
AbstractThe purpose of this paper is to introduce and analyze an extragradient method with regulariz...
AbstractLet C and Q be nonempty closed convex sets in Rn and Rm, respectively, and A an m by n real ...
We consider simple projection methods for solving convex feasibility problems. Both successive and s...
Given closed convex sets $C_i$, $i=1,\ldots,\ell$, and some nonzero linear maps $A_i$, $i = 1,\ldots...
The multiple-sets split feasibility problem (MSFP) captures various applications arising in many are...