Sparsified Adaptive Cross Approximation Algorithm for Accelerated Method of Moments Computations
| Autor: | Carine Simon, Alexander Heldring, Eduard Ubeda, Juan M. Rius, J. M. Tamayo |
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| Přispěvatelé: | Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions, Universitat Politècnica de Catalunya. ANTENNALAB - Grup d'Antenes i Sistemes Radio |
| Rok vydání: | 2013 |
| Předmět: |
Mathematical optimization
Impedance matrix compression impedance matrix compression Computational complexity theory Iterative method Method of moments Basis function Numerical simulation Antenes de microones Method of moments (statistics) Electromagnetisme Microwave antennas Electromagnetism Fast solvers Electrical and Electronic Engineering Mathematics Sparse matrix Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Antenes i agrupacions d'antenes [Àrees temàtiques de la UPC] Approximation theory fast solvers method of moments Linear system Approximation algorithm Computational electromagnetics Mathematics::Logic numerical simulation Algorithm |
| Zdroj: | UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) Recercat. Dipósit de la Recerca de Catalunya instname Digital.CSIC. Repositorio Institucional del CSIC |
| ISSN: | 1558-2221 0018-926X 2009-1389 |
| DOI: | 10.1109/tap.2012.2215292 |
| Popis: | 7 pages, 8 figures, 5 tables.-- © 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works This paper presents a modification of the adaptive cross approximation (ACA) algorithm for accelerated solution of the Method of Moments linear system for electrically large radiation and scattering problems. As with ACA, subblocks of the impedance matrix that represent the interaction between well separated subdomains are substituted by ¿compressed¿ approximations allowing for reduced storage and accelerated iterative solution. The modified algorithm approximates the original subblocks with products of sparse matrices, constructed with the aid of the ACA algorithm and of a sub-sampling of the original basis functions belonging to either subdomain. Because of the sampling, an additional error is introduced with respect to ACA, but this error is controllable. Just like ordinary ACA, sparsified ACA is kernel-independent and needs no problem-specific information, except for the topology of the basis functions. As a numerical example, RCS computations of the NASA almond are presented, showing an important gain in efficiency. Furthermore, the numerical experiment reveals a computational complexity close to $N log N$ for sparsified ACA for a target electrical size of up to 50 wavelengths This work was supported by the Spanish Interministerial Commission on Science and Technology (CICYT) under projects TEC2009-13897-C03-01, TEC2010-20841-C04- 02 and CONSOLIDER CSD2008-00068 and through the Ramon y Cajal program |
| Databáze: | OpenAIRE |
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