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首页> 外文期刊>Applied Computational Electromagnetics Society journal >Novel Reduced Matrix Equation Constructing Method Accelerates Iterative Solution of Characteristic Basis Function Method
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Novel Reduced Matrix Equation Constructing Method Accelerates Iterative Solution of Characteristic Basis Function Method

机译:简化矩阵方程构造的新方法加速了特征基函数法的迭代求解

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摘要

In this paper, a new construction method of reduced matrix equation is proposed to improve the iterative solution efficiency of characteristic basis function method (CBFM). Firstly, the singular value decomposition (SVD) technique is applied to compress the incident excitations and these new excitations retained on each block after SVD are defined as the excitation basis functions (EBFs). Then, the characteristic basis functions (CBFs) of each block are solved from these EBFs. Lastly, these EBFs and CBFs are used as the testing functions and the basis functions to construct the reduction matrix equation, respectively. The diagonal sub-matrices of the reduced matrix constructed by the proposed method are all identity matrices. Thus, the condition of the reduced matrix is improved resulting in a smaller number of iterations required for the solution of the reduced matrix equation. The numerical results validate the accuracy of the proposed method. Compared with the traditional CBFM, the iterative solution efficiency of the reduced matrix equation constructed by the proposed method is significantly improved.
机译:为了提高特征基函数法(CBFM)的迭代求解效率,提出了一种简化的矩阵方程组的构造方法。首先,使用奇异值分解(SVD)技术来压缩入射激励,并将这些在SVD之后保留在每个块上的新激励定义为激励基函数(EBF)。然后,从这些EBF求解每个块的特征基函数(CBF)。最后,将这些EBF和CBF分别用作检验函数和基函数,以构造约简矩阵方程。该方法构造的约简矩阵的对角子矩阵均为恒等矩阵。因此,简化矩阵的条件得到改善,从而导致求解简化矩阵方程式所需的迭代次数更少。数值结果验证了该方法的准确性。与传统的CBFM相比,该方法构造的约简矩阵方程的迭代求解效率大大提高。

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