We study the finite convergence of iterative methods for solving convex feasibility problems. Our key assumptions are that interior solution set is nonempty and certain overrelaxation parameters converge to zero, but with a rate slower than any geometric sequence. Unlike other works in this area, which require divergent series overrelaxations, our approach allows us consider some summable serie...

Solving dense linear systems of equations is quite time consuming and requires an efficient parallel implementation on powerful supercomputers. Du, Zheng Wang presented some new iterative methods for [Journal Applied Analysis Computation, 2011, 1(3): 351-360]. This paper shows that their are suitable solving system equations, compared with the classical Jacobi Gauss-Seidel methods.

In this work, a new iterative method is proposed for obtaining the approximate solution of a class of Hammerstein type Integral Equations System. The main structure of this method is based on the Richardson iterative method for solving an algebraic linear system of equations. Some conditions for existence and unique solution of this type equations are imposed. Convergence analysis and error bou...

This paper gives a new approach to decoding Hermite codes using the key equation, avoiding the use of majority voting. Our approach corrects up to (dmin − 1)/2 errors, and works up to some extent also beyond. We present an efficient implementation of our algorithm based on a Sugiyamatype iterative procedure for computing solutions of a key equation.

‎In this paper‎, ‎we propose two preconditioned AOR iterative methods to solve systems of linear equations whose coefficient matrices are Z-matrix‎. ‎These methods can be considered as improvements of two previously presented ones in the literature‎. ‎Finally some numerical experiments are given to show the effectiveness of the proposed preconditioners‎.‎