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Abstract: The nonlinear complementarity problem can be reformulated as a nonsmooth equation. In this paper we propose a new smoothing quasi-Newton method for the solution of the nonlinear complementarity problems by constructing a new smoothing approximation function. Global and local superlinear convergence results of the proposed algorithm are established under suitable conditions. Some numerical results are reported in the paper. [Copyright &y& Elsevier]

Abstract: In this paper, a practical bivariate Newton–Thiele type matrix Padé approximation is introduced by using the generalized inverse of a matrix. The approximants are expressed in the form of Newton expansion and branched continued fractions, which can be computed by an efficient recursive algorithm. Some algebraic properties are also discussed and the application in state-space realization of the 2-D filters is given in the end. [Copyright &y& Elsevier]

Abstract: In this paper we present a novel fast mesh parameterization algorithm based on subdivision scheme. First, an algorithm of approximating a given triangular mesh by the 4-point interpolatory subdivision is proposed, then a mesh parameterization method is developed based on the subdivision surface approximation algorithm. The novel mesh parameterization method is a generalization of the chordal parameterization to surface case, and it is more computationally efficient than previous methods because it obviates any computation of linear system of equations. Some numerical experiments show the efficiency of the novel algorithm. [Copyright &y& Elsevier]

Abstract: In this paper, we propose a compact alternating direction implicit (ADI) scheme for solving the two-dimensional parabolic equation. The maximum norm convergence is proven, and the convergence rate is second-order in time and fourth-order in space. We develop a Richardson extrapolation algorithm to increase the accuracy to sixth-order both in time and space. Numerical experiments show the effectiveness of the method. [Copyright &y& Elsevier]

Abstract: To solve a general class of elliptic operator equations, Cohen et al. (2001) [2] designed two adaptive wavelet algorithms that yield an approximate solution with error . In this paper, we modify the error analysis for the second algorithm and optimize the upper bound. Numerical experiments demonstrate that our approximation has some advantages compared to that of the reference. [Copyright &y& Elsevier]

Abstract: In this paper a modified gradient based algorithm for solving Sylvester equations is presented. Different from the gradient based method introduced by Ding and Chen and the relaxed gradient based algorithm proposed by Niu et al. , the information generated in the first half-iterative step is fully exploited and used to construct the approximate solution. Theoretical analysis shows that the new method converges under certain assumptions. Numerical results are given to verify the efficiency of the new method. [Copyright &y& Elsevier]

Abstract: In this paper, two iterative algorithms are proposed to solve the linear matrix equations . When the matrix equations are consistent, by the first algorithm, a solution can be obtained within finite iterative steps in the absence of roundoff-error for any initial value, furthermore, the minimum-norm solution can be got by choosing a special kind of initial matrix. Additionally, the unique optimal approximation solution to a given matrix can be derived by finding the minimum-norm solution of a new matrix equations . When the matrix equations are inconsistent, we present the second algorithm to find the least-squares solution with the minimum-norm. Finally, two numerical examples are tested by MATLAB, the results show that these iterative algorithms are efficient. [Copyright &y& Elsevier]

Abstract: This paper describes a numerical approximation to the solution of Volterra integral equations of the second kind. This algorithm combines trapezoidal and Simpson rules. We prove the convergence of the method. Numerical examples are provided to illustrate the accuracy of the method. [Copyright &y& Elsevier]

Abstract: In this paper we propose an iterative algorithm to solve large size linear inverse ill posed problems. The regularization problem is formulated as a constrained optimization problem. The dual Lagrangian problem is iteratively solved to compute an approximate solution. Before starting the iterations, the algorithm computes the necessary smoothing parameters and the error tolerances from the data. The numerical experiments performed on test problems show that the algorithm gives good results both in terms of precision and computational efficiency. [Copyright &y& Elsevier]

Abstract: In this paper we propose a new method of investigating the change of dynamics in reaction–diffusion equations, which is based on approximating the Euclidian norm of state variables along with the introduction of phase space. Our method is simple in implementation and can be applied to study the dynamics of multiple spirals. The method is extended to study the stability of spiral waves by developing an algorithm which is applied to circular and meandering motions. [Copyright &y& Elsevier]

Abstract: Let R and S be m × m and n × n nontrivial real symmetric involutions. An m × n complex matrix A is termed (R, S)-conjugate if , where denotes the conjugate of A. In this paper, necessary and sufficient conditions are established for the existence of the (R, S)-conjugate solution to the system of matrix equations AX = C and XB = D. The expression is also presented for such solution to this system. In addition, the explicit expression of this solution to the corresponding optimal approximation problem is obtained. Furthermore, the least squares (R, S)-conjugate solution with least norm to this system mentioned above is considered. The representation of such solution is also derived. Finally an algorithm and numerical examples are given. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, by solving the relaxed quasiconcave programming problem in outcome space, a new global optimization algorithm for convex multiplicative programming is presented. Two kinds of techniques are employed to establish the algorithm. The first one is outer approximation technique which is applied to shrink relaxation area of quasiconcave programming problem and to compute appropriate feasible points and to raise the capacity of bounding. And the other one is branch and bound technique which is used to guarantee global optimization. Some numerical results are presented to demonstrate the effectiveness and feasibility of the proposed algorithm. [Copyright &y& Elsevier]

Abstract: In this paper, we extend the algorithm in Xue and Cheng [L. Xue, X.L. Cheng, An algorithm for solving the obstacle problems, Comput. Math. Appl. 48 (2004) 1651–1657] for solving the double obstacle problem. We try to find the approximated region of the contact in the double obstacle problem with less computation time by iteration. Numerical example is given for the double obstacle problem for the elastic–plastic torsion problem to support the algorithm. [Copyright &y& Elsevier]