Sparsening Conformal Arrays Through a Versatile BCS-Based Method
Sparsening conformal arrangements is carried out through a versatile Multi-Task Bayesian Compressive Sensing (MT-BCS) strategy. The problem, formulated in a probabilistic fashion as a pattern-matching synthesis, is that of determining the sparsest excitation set (locations and weights) fitting a ref...
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| Vydáno v: | IEEE transactions on antennas and propagation Ročník 62; číslo 4; s. 1681 - 1689 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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IEEE
01.04.2014
Institute of Electrical and Electronics Engineers |
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| ISSN: | 0018-926X, 1558-2221 |
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| Abstract | Sparsening conformal arrangements is carried out through a versatile Multi-Task Bayesian Compressive Sensing (MT-BCS) strategy. The problem, formulated in a probabilistic fashion as a pattern-matching synthesis, is that of determining the sparsest excitation set (locations and weights) fitting a reference pattern subject to user-defined geometrical constraints. Results from a set of representative numerical experiments are presented to illustrate the key-features of the proposed approach as well as to assess, also through comparisons, its potentials in terms of matching accuracy, element saving, and computational costs. |
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| AbstractList | Sparsening conformal arrangements is carried out through a versatile Multi-Task Bayesian Compressive Sensing openbracket MT - BCS [ closebracket ] strategy. The problem, formulated in a probabilistic fashion as a pattern-matching synthesis, is that of determining the sparsest excitation set (locations and weights) fitting a reference pattern subject to user-defined geometrical constraints. Results from a set of representative numerical experiments are presented to illustrate the key-features of the proposed approach as well as to assess, also through comparisons, its potentials in terms of matching accuracy, element saving, and computational costs. Sparsening conformal arrangements is carried out through a versatile Multi-Task Bayesian Compressive Sensing (MT-BCS) strategy. The problem, formulated in a probabilistic fashion as a pattern-matching synthesis, is that of determining the sparsest excitation set (locations and weights) fitting a reference pattern subject to user-defined geometrical constraints. Results from a set of representative numerical experiments are presented to illustrate the key-features of the proposed approach as well as to assess, also through comparisons, its potentials in terms of matching accuracy, element saving, and computational costs. |
| Author | Oliveri, Giacomo Robol, Fabrizio Massa, Andrea Bekele, Ephrem T. |
| Author_xml | – sequence: 1 givenname: Giacomo surname: Oliveri fullname: Oliveri, Giacomo email: giacomo.oliveri@disi.unitn.it organization: DISI, Univ. of Trento, Trento, Italy – sequence: 2 givenname: Ephrem T. surname: Bekele fullname: Bekele, Ephrem T. email: bekele@disi.unitn.it organization: DISI, Univ. of Trento, Trento, Italy – sequence: 3 givenname: Fabrizio surname: Robol fullname: Robol, Fabrizio email: fabrizio.robol@disi.unitn.it organization: DISI, Univ. of Trento, Trento, Italy – sequence: 4 givenname: Andrea surname: Massa fullname: Massa, Andrea email: andrea.massa@unitn.it organization: DISI, Univ. of Trento, Trento, Italy |
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| References | ref35 ref13 ref34 ref12 ref15 ref14 ref31 ref30 ref33 ref11 ref32 ref10 ref2 balanis (ref39) 1997 ref17 ref38 ref16 ref19 tipping (ref26) 2001; 56 ref18 mailloux (ref1) 2007 ref24 ref23 ref25 ji (ref37) 0 ref20 ref22 ref21 ref28 ref27 ref29 ref8 tipping (ref36) 2003 ref7 tennant (ref6) 1995; 31 ref9 ref4 ref3 ref5 |
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| SubjectTerms | Antennas Apertures Arrays Bayes methods Bayesian analysis Bayesian compressive sampling Computational efficiency conformal arrays constrained array synthesis Electromagnetism Engineering Sciences Fittings Indexes Layout Merging Pattern matching Probability theory sparse arrays Strategy Synthesis Vectors |
| Title | Sparsening Conformal Arrays Through a Versatile BCS-Based Method |
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