Guangbin Wang

Qingdao University of Science and Technology, Tsingtao, Shandong Sheng, China

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Publications (13)4.37 Total impact

  • Guangbin Wang, Ting Wang, Fuping Tan
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    ABSTRACT: In this paper, we present preconditioned generalized accelerated overrelaxation methods. We compare the spectral radii of the iteration matrices of the preconditioned and original methods. The comparison results show that the preconditioned GAOR methods converge faster than the GAOR method whenever the GAOR method is convergent. Finally, we present two numerical examples to confirm our theoretical results.
    Applied Mathematics and Computation 02/2013; 219(11):5811–5816. · 1.35 Impact Factor
  • Guangbin Wang, Fuping Tan
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    ABSTRACT: We present a preconditioned mixed-type splitting iterative method for solving the linear system Ax=b, where A is a Z-matrix. We give some comparison theorems to show that the rate of convergence of the preconditioned mixed-type splitting iterative method is faster than that of the mixed-type splitting iterative method. Finally, we give one numerical example to illustrate our results.
    Advances in Numerical Analysis. 01/2013; 2013.
  • Guangbin Wang, Ting Wang, Fuping Tan, Shuqian Shen
    Chiang Mai Journal of Science 01/2013; 40(4). · 0.52 Impact Factor
  • Guangbin Wang, Yanli Du, Fuping Tan
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    ABSTRACT: We present preconditioned generalized accelerated overrelaxation methods for solving weighted linear least square problems. We compare the spectral radii of the iteration matrices of the preconditioned and the original methods. The comparison results show that the preconditioned GAOR methods converge faster than the GAOR method whenever the GAOR method is convergent. Finally, we give a numerical example to confirm our theoretical results.
    Journal of Applied Mathematics 01/2012; 2012. · 0.83 Impact Factor
  • Guangbin Wang, Ting Wang, Yanli Du
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    ABSTRACT: We present some sufficient conditions on convergence of AOR method for solving Ax=b with A being a strictly doubly α diagonally dominant matrix. Moreover, we give two numerical examples to show the advantage of the new results.
    Journal of Applied Mathematics 01/2012; 2012. · 0.83 Impact Factor
  • Guangbin Wang, Ning Zhang
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    ABSTRACT: In this paper, we present a new preconditioned AOR-type iterative method for solving the linear system Ax=b, where A is a Z-matrix, and prove its convergence. Then we give some comparison theorems to show that the rate of convergence of the In this paper, we present a new preconditioned AOR-type iterative method for solving the linear system Ax=b, where A is a Z-matrix, and prove its convergence. Then we give some comparison theorems to show that the rate of convergence of the preconditioned AOR-type iterative method is faster than the rate of convergence of the AOR-type iterative method. Finally, preconditioned AOR-type iterative method is faster than the rate of convergence of the AOR-type iterative method. Finally, we give two numerical examples to illustrate our results. we give two numerical examples to illustrate our results. KeywordsZ-matrix–AOR-type iterative method–Precondition–Comparison theorem–Linear system KeywordsZ-matrix–AOR-type iterative method–Precondition–Comparison theorem–Linear system
    Journal of Applied Mathematics and Computing 01/2011; 37(1):103-117.
  • Guangbin Wang, Hao Wen, Ting Wang
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    ABSTRACT: We discuss the convergence of GAOR method for linear systems with strictly $\alpha$ diagonally dominant matrices. Moreover, we show that our results are better than ones of Darvishi and Hessari (2006), Tian et al. (2008) by using three numerical examples.
    Journal of Applied Mathematics 01/2011; · 0.83 Impact Factor
  • Guangbin Wang, Hao Wen, Liangliang Li, Xue Li
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    ABSTRACT: In this paper, we obtain bounds for the spectral radius of the matrix lω,r which is the iterative matrix of the generalized accelerated overrelaxation (GAOR) iterative method. Moreover, we present one convergence theorem of the GAOR method. Finally, we present two numerical examples.
    Applied Mathematics and Computation. 01/2011; 217:7509-7514.
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    Guangbin Wang, Ning Zhang, Fuping Tan
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    ABSTRACT: In this paper, we present a preconditioned AOR-type iterative method for solving the linear systems Ax = b, where A is a Z-matrix. And give some comparison theorems to show that the rate of convergence of the preconditioned AOR-type iterative method is faster than the rate of convergence of the AOR-type iterative method. Keywords—Z-matrix, AOR-type iterative method, precondition, comparison.
    01/2010;
  • Guangbin Wang, Fuping Tan
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    ABSTRACT: Climent and Perea [J.-J. Climent, C. Perea, Convergence and comparison theorems for a generalized alternating iterative method, Appl. Math. Comput. 143 (2003) 1–14] introduced a generalized alternating iterative method. In this paper, we establish convergence results for a nonsingular H-matrix, upper bound to the spectral radius of iterative matrix and comparison theorem for a monotone matrix. Moreover, we give some numerical examples to show our results.
    Applied Mathematics and Computation. 01/2009; 210:100-106.
  • Guangbin Wang, Hao Wen, Fuping Tan
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    ABSTRACT: In this paper, we consider synchronous stationary and nonstationary multi-splitting Schwarz methods for solving the linear complementarity problems. Moreover, We establish two convergence theorems of the methods by using the concept of H-compatible splitting.
    2008 International Symposium on Computer Science and Computational Technology, ISCSCT 2008, 20-22 December 2008, Shanghai, China, 2 Volumes; 01/2008
  • Guangbin Wang, Fuping Tan
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    ABSTRACT: In this paper, the parallel alternating algorithm for solving the system of linear equations Ax = b is investigated. The convergence result for the method is given when the coefficient matrix is a nonsingular H-matrix.
    01/2008;
  • Guangbin Wang, Xue Li, Fuping Tan
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    ABSTRACT: In this paper, we present some new upper bounds for the spectral radius of iterative matrices based on the concept of doubly α diagonally dominant matrix. And subsequently, we give two examples to show that our results are better than the earlier ones. Keywords—doubly α diagonally dominant matrix, eigenvalue, iterative matrix, spectral radius, upper bound.