Accelerated characteristic basis functions generation of large block with Sherman‐Morrison‐Woodbury algorithm and characteristic basis function method

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.