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Principal Component Analysis Enhanced CBFM for Solving Monostatic Scattering Problems of Object

机译:主成分分析增强了CBFM,用于解决物体的单体散射问题

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In order to improve the efficiency of characteristic basis function method for analyzing the monostatic scattering problems, the principal component analysis (PCA) is used to compress the excitation matrix, then the number of the matrix equation solutions is reduced because of the reduced number of excitation. Secondly, a merged characteristic basis functions (CBFs) method is proposed by considering the mutual interaction among adjacent blocks. The number of matrix equation solutions and the number of CBFs are both reduced by using proposed method. Numerical examples verify and demonstrate that the proposed method is accuracy and efficiency.
机译:为了提高特征基函数方法的效率,用于分析单体散射问题,主要成分分析(PCA)用于压缩激励矩阵,然后由于累积的激励数量减少而减少了矩阵方程溶液的数量。其次,通过考虑相邻块之间的相互交互来提出合并的特征基函数(CBFS)方法。通过使用所提出的方法,矩阵方程解决方案的数量和CBF的数量均均降低。数值示例验证并证明所提出的方法是准确性和效率。

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