In order to reduce the storage amount for the sparse coefficient matrix in pre-corrected fast Fourier transform （P-FFT） or fitting the Green function fast Fourier transform （FG-FFT）, the real coefficients are solv...In order to reduce the storage amount for the sparse coefficient matrix in pre-corrected fast Fourier transform （P-FFT） or fitting the Green function fast Fourier transform （FG-FFT）, the real coefficients are solved by improving the solution method of the coefficient equations. The novel method in both P-FFT and FG-FFT for the electric field integral equation （EFIE） is employed. With the proposed method, the storage amount for the sparse coefficient matrix can be reduced to the same level as that in the adaptive integral method （AIM） or the integral equation fast Fourier transform （IE-FFT）. Meanwhile, the new algorithms do not increase the number of the FFTs used in a matrix-vector product, and maintain almost the same level of accuracy as the original versions. Besides, in respect of the time cost in each iteration, the new algorithms have also the same level as AIM （or IE- FFF）. The numerical examples demonstrate the advantages of the proposed method.展开更多
基金The National Basic Research Program of China(973Program)(No.2013CB329002)
文摘In order to reduce the storage amount for the sparse coefficient matrix in pre-corrected fast Fourier transform （P-FFT） or fitting the Green function fast Fourier transform （FG-FFT）, the real coefficients are solved by improving the solution method of the coefficient equations. The novel method in both P-FFT and FG-FFT for the electric field integral equation （EFIE） is employed. With the proposed method, the storage amount for the sparse coefficient matrix can be reduced to the same level as that in the adaptive integral method （AIM） or the integral equation fast Fourier transform （IE-FFT）. Meanwhile, the new algorithms do not increase the number of the FFTs used in a matrix-vector product, and maintain almost the same level of accuracy as the original versions. Besides, in respect of the time cost in each iteration, the new algorithms have also the same level as AIM （or IE- FFF）. The numerical examples demonstrate the advantages of the proposed method.
