• Journal of applied mathematics & informatics
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• v.23 no.1_2
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• pp.183-191
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• 2007

In this paper, we introduce and study a new class of equilibrium problems, known as regularized mixed quasi equilibrium problems. We use the auxiliary principle technique to suggest and analyze some iterative schemes for regularized equilibrium problems. We prove that the convergence of these iterative methods requires either pseudomonotonicity or partially relaxed strongly monotonicity. Our proofs of convergence are very simple. As special cases, we obtain earlier results for solving equilibrium problems and variational inequalities involving the convex sets.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.314-317
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• 1993

In this paper, the IPE(Iterative Parameter Estimation) methods for the nonlinear measurements are proposed. The IPE methods convert the problems of the parameter estimation for the nonlinear measurements to that of the solution of the nonlinear equations approximately and use several iterative numerical solutions, such as fixed points theory, Newton's methods, quasi-Newton's methods and steepest descent techniques. the IPE methods for the nonlinear measurements-in the case of the error estimation for the inertial navigation systems are simulated, and it is found that the estimation errors for the nonlinear measurements decrease rapidly and converge to almost that of the linear LSE(Least Squares Estimation) when the IPE methods are applied.

• International Journal of Naval Architecture and Ocean Engineering
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• v.9 no.4
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• pp.390-403
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• 2017

Smoothed Particle Hydrodynamics (SPH) method has a good adaptability for the simulation of free surface flow problems. There are two forms of SPH. One is weak compressible SPH and the other one is incompressible SPH (ISPH). Compared with the former one, ISPH method performs better in many cases. ISPH based on Rankine source solution can perform better than traditional ISPH, as it can use larger stepping length by avoiding the second order derivative in pressure Poisson equation. However, ISPH_R method needs to solve the sparse linear matrix for pressure Poisson equation, which is one of the most expensive parts during one time stepping calculation. Iterative methods are normally used for solving Poisson equation with large particle numbers. However, there are many iterative methods available and the question for using which one is still open. In this paper, three iterative methods, CGS, Bi-CGstab and GMRES are compared, which are suitable and typical for large unsymmetrical sparse matrix solutions. According to the numerical tests on different cases, still water test, dam breaking, violent tank sloshing, solitary wave slamming, the GMRES method is more efficient than CGS and Bi-CGstab for ISPH method.

• Korean Journal of Mathematics
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• v.4 no.2
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• pp.83-88
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• 1996

In 1994 Z.Liang constructed an iterative method for the solution of nonlinear equations involving m-accretive operators in uniformly smooth Banach spaces. In this paper we apply the slight variants of Liang's iterative methods and generalize the results of Z.Liang. Moreover our proof is more simple than Liang's proof.

• Journal of applied mathematics & informatics
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• v.27 no.1_2
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• pp.1-12
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• 2009

Iterative algorithms are proposed for the least-squares symmetric solution of AXB = E with a submatrix constraint. We characterize the linear mappings from their independent element space to the constrained solution sets, study their properties and use these properties to propose two matrix iterative algorithms that can find the minimum and quasi-minimum norm solution based on the classical LSQR algorithm for solving the unconstrained LS problem. Numerical results are provided that show the efficiency of the proposed methods.

• Korean Journal of Mathematics
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• v.18 no.3
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• pp.299-309
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• 2010

In this paper, we study the first order nonlinear neutral difference equation: $${\Delta}(x(n)+px(n-{\tau}))+f(n,x(n-c),x(n-d))=r(n),\;n{\geq}n_0$$. Using the Banach fixed point theorem, we prove the existence of bounded positive solutions of the equation, suggest Mann iterative schemes of bounded positive solutions, and discuss the error estimates between bounded positive solutions and sequences generated by Mann iterative schemes.

• Journal of applied mathematics & informatics
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• v.17 no.1_2_3
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• pp.59-72
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• 2005

The auxiliary principle is used to suggest and analyze some iterative methods for solving solving hemivariational inequalities under mild conditions. The results obtained in this paper can be considered as a novel application of the auxiliary principle technique. Since hemivariational in­equalities include variational inequalities and nonlinear optimization problems as special cases, our results continue to hold for these problems.

• Kyungpook Mathematical Journal
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• v.50 no.1
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• pp.7-14
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• 2010

In this paper, we construct some improvements of the Jarratt method for solving non-linear equations. A new sixth-order method are developed and numerical examples are given to support that the method obtained can compete with other sixth-order iterative methods.

• Journal of applied mathematics & informatics
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• v.6 no.1
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• pp.89-98
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• 1999

We propose some new iterative methods for solving the generalized variational inequalities where the underlying operator T is monotone. These methods may be viewed as projection-type meth-ods. Convergence of these methods requires that the operator T is only monotone. The methods and the proof of the convergence are very simple. The results proved in this paper also represent a signif-icant improvement and refinement of the known results.

• Journal of Advanced Navigation Technology
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• v.13 no.1
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• pp.62-67
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• 2009

The demand for high performance computer grows to solve large linear systems of equations in such engineering fields - circuit simulation for VLSI design, image processing, structural engineering, aerodynamics, etc. Many various parallel processing systems have been proposed and manufactured to satisfy the demand. The properties of linear system determine what algorithm is proper to solve the problem. Direct methods or iterative methods can be used for solving the problem. In this paper, an intelligent parallel iterative method for solving linear systems of equations with large sparse matrices is proposed and its efficiency is proved through simulation.