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块三对角阵分解因子的估值与应用 被引量:1

EVALUATING THE FACTORS OF BLOCK TRIDIAGONAL MATRIX AND ITS APPLICATION
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摘要 In this paper, we first introduce the situation of Incomplete Factorization(IF)preconditioners. Consequently, we reduce the block tridiagonal matrix with non-singular off-diagonal blocks into a model one that has only negative identity matrixfor its off-diagonals. Then we evaluate the block LU factors for the model with thehelp of M matrices. The analyses show that the evaluation is exact in some sense.For the matrices which have equal diagonal blocks and have only negative identityoff-diagonal blocks, the tendency of the factors are also focused on. Moreover,we construct a type of preconditioners with these evaluations and analyze thecondition number of the preconditioned matrices. For the model problem, we givethe evaluation and practical condition number, which shows that the evaluation isexact to some extent. At last, we implement four of these preconditioners and testthem for the model problem. The results show that our method is effective and theanalyses imply that they will be more efficient than others in parallel computing. In this paper, we first introduce the situation of Incomplete Factorization(IF) preconditioners. Consequently, we reduce the block tridiagonal matrix with non-singular off-diagonal blocks into a model one that has only negative identity matrix for its off-diagonals. Then we evaluate the block LU factors for the model with the help of M matrices. The analyses show that the evaluation is exact in some sense. For the matrices which have equal diagonal blocks and have only negative identity off-diagonal blocks, the tendency of the factors are also focused on. Moreover, we construct a type of preconditioners with these evaluations and analyze the condition number of the preconditioned matrices. For the model problem, we give the evaluation and practical condition number, which shows that the evaluation is exact to some extent. At last, we implement four of these preconditioners and test them for the model problem. The results show that our method is effective and the analyses imply that they will be more efficient than others in parallel computing.
出处 《计算数学》 CSCD 北大核心 2002年第3期283-290,共8页 Mathematica Numerica Sinica
关键词 块三对角阵 分解因子 估值 应用 M矩阵 块LU分解 不完全解解 预条件子 并行算法 M matrix,block LU factorization,incomplete factorization,preconditioner,parallel algorithm
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