A better compression rate of the characteristic basis function method (CBFM) can be obtained by increasing the block size to generate the characteristic basis functions (CBFs). However, it has been heavy to generate the CBFs for electrically large-size blocks in the case of multiple excitations with traditional CBFM. In this paper, a novel computing scheme, accelerated generation method that combined the traditional CBFM with the Sherman-Morrison-Woodbury algorithm (SMWA) is proposed to generate CBFs and calculate the reduced impedance matrix. Furthermore, a recursive process of the computing scheme is introduced to accelerate the performance. Finally, the computational results are validated and performed that the proposal method is more effective than the conventional methods.

中文翻译：

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使用 Sherman-Morrison-Woodbury 算法和特征基函数法加速大块的特征基函数生成

通过增加块大小来生成特征基函数（CBF），可以获得更好的特征基函数方法（CBFM）的压缩率。然而，在使用传统 CBFM 进行多次激发的情况下，为电大尺寸块生成 CBF 是很困难的。在本文中，提出了一种新的计算方案，即结合传统CBFM和Sherman-Morrison-Woodbury算法（SMWA）的加速生成方法来生成CBF并计算约简阻抗矩阵。此外，引入了计算方案的递归过程以加速性能。最后，计算结果得到验证和执行，建议方法比传统方法更有效。