Browsing by Subject "Recompression"

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    Algebraic acceleration and regularization of the source reconstruction method with the recompressed adaptive cross approximation
    (IEEE, 2014) Kazempour, Mahdi; Gürel, Levent
    We present a compression algorithm to accelerate the solution of source reconstruction problems that are formulated with integral equations and defined on arbitrary three-dimensional surfaces. This compression technique benefits from the adaptive cross approximation (ACA) algorithm in the first step. A further error-controllable recompression is applied after the ACA. The numerical results illustrate the efficiency and accuracy of the proposed method. © 2014 IEEE.
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    Fast solutions of multiple monostatic radar cross section problems using the recompressed adaptive cross approximation algorithm
    (2014-01) Kazempourradi, Seyed Mahdi
    We developed a method that incorporates an algebraic compression technique to accelerate the computation of multiple monostatic radar cross sections (RCSs) of arbitrary 3-D geometries. Since most radars rely on the backscattering from a target, computing the monostatic RCS (MRCS) is needed more often than the bistatic RCS. Computation of each MRCS value requires a separate solution, which may be costly depending on the size of the problem. The task becomes considerably harder when the goal is to compute multiple MRCS values with high angular resolution. The proposed technique compresses the excitation matrix using the adaptive cross approximation (ACA) algorithm in the rst step. A recompression is applied on the matrices obtained from ACA by utilizing the QR decomposition and computing the singular value decomposition in an e - cient manner. The solution of each excitation is accelerated by the multilevel fast multipole algorithm. The numerical results demonstrate the e ciency and accuracy of our proposed method.