Bioinspired multiobjective synthesis of X-band FSS via general regression neural network and cuckoo search algorithm
ABSTRACT A bioinspired hybrid multiobjective optimization technique that associates a general regression neural network and a cuckoo search algorithm is proposed for microwave applications. This study is focused on the simulation, design, and synthesis of frequency selective surfaces (FSSs) with tri...
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| Veröffentlicht in: | Microwave and optical technology letters 2015-10, Vol.57 (10), p.2400-2405 |
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| container_issue | 10 |
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| container_title | Microwave and optical technology letters |
| container_volume | 57 |
| creator | Neto, M. C. Alcantara Araújo, J. P. L. Barros, F. J. B. Silva, A. N. Cavalcante, G. P. S. D'Assunção, A. G. |
| description | ABSTRACT
A bioinspired hybrid multiobjective optimization technique that associates a general regression neural network and a cuckoo search algorithm is proposed for microwave applications. This study is focused on the simulation, design, and synthesis of frequency selective surfaces (FSSs) with triangular ring patch elements printed on fiberglass substrates (FR4). The proposed technique aims, for example, to design FSSs with specific values for the resonance frequency and bandwidth in the frequency range from 8 to 12 GHz. For validation purpose, a bandstop FSS filter, centered at 11 GHz and with a 4 GHz bandwidth, was synthesized, fabricated, and measured. Good agreement between simulated and measured results is reported. © 2015 Wiley Periodicals, Inc. Microwave Opt Technol Lett 57:2400–2405, 2015 |
| doi_str_mv | 10.1002/mop.29349 |
| format | Article |
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A bioinspired hybrid multiobjective optimization technique that associates a general regression neural network and a cuckoo search algorithm is proposed for microwave applications. This study is focused on the simulation, design, and synthesis of frequency selective surfaces (FSSs) with triangular ring patch elements printed on fiberglass substrates (FR4). The proposed technique aims, for example, to design FSSs with specific values for the resonance frequency and bandwidth in the frequency range from 8 to 12 GHz. For validation purpose, a bandstop FSS filter, centered at 11 GHz and with a 4 GHz bandwidth, was synthesized, fabricated, and measured. Good agreement between simulated and measured results is reported. © 2015 Wiley Periodicals, Inc. Microwave Opt Technol Lett 57:2400–2405, 2015</description><identifier>ISSN: 0895-2477</identifier><identifier>EISSN: 1098-2760</identifier><identifier>DOI: 10.1002/mop.29349</identifier><identifier>CODEN: MOTLEO</identifier><language>eng</language><publisher>New York: Blackwell Publishing Ltd</publisher><subject>Bandwidth ; bioinspired computing ; Computer simulation ; frequency selective surface ; general regression neural network ; General regression neural networks ; Microwaves ; multiobjective cuckoo search ; Optimization ; Search algorithms ; Synthesis ; X-band</subject><ispartof>Microwave and optical technology letters, 2015-10, Vol.57 (10), p.2400-2405</ispartof><rights>2015 Wiley Periodicals, Inc.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4019-6e182d97bbe2ba524c63cf0e233d940a3bf8c8e47f0db08aa6d235debec1fb993</citedby><cites>FETCH-LOGICAL-c4019-6e182d97bbe2ba524c63cf0e233d940a3bf8c8e47f0db08aa6d235debec1fb993</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fmop.29349$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fmop.29349$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids></links><search><creatorcontrib>Neto, M. C. Alcantara</creatorcontrib><creatorcontrib>Araújo, J. P. L.</creatorcontrib><creatorcontrib>Barros, F. J. B.</creatorcontrib><creatorcontrib>Silva, A. N.</creatorcontrib><creatorcontrib>Cavalcante, G. P. S.</creatorcontrib><creatorcontrib>D'Assunção, A. G.</creatorcontrib><title>Bioinspired multiobjective synthesis of X-band FSS via general regression neural network and cuckoo search algorithm</title><title>Microwave and optical technology letters</title><addtitle>Microw. Opt. Technol. Lett</addtitle><description>ABSTRACT
A bioinspired hybrid multiobjective optimization technique that associates a general regression neural network and a cuckoo search algorithm is proposed for microwave applications. This study is focused on the simulation, design, and synthesis of frequency selective surfaces (FSSs) with triangular ring patch elements printed on fiberglass substrates (FR4). The proposed technique aims, for example, to design FSSs with specific values for the resonance frequency and bandwidth in the frequency range from 8 to 12 GHz. For validation purpose, a bandstop FSS filter, centered at 11 GHz and with a 4 GHz bandwidth, was synthesized, fabricated, and measured. Good agreement between simulated and measured results is reported. © 2015 Wiley Periodicals, Inc. Microwave Opt Technol Lett 57:2400–2405, 2015</description><subject>Bandwidth</subject><subject>bioinspired computing</subject><subject>Computer simulation</subject><subject>frequency selective surface</subject><subject>general regression neural network</subject><subject>General regression neural networks</subject><subject>Microwaves</subject><subject>multiobjective cuckoo search</subject><subject>Optimization</subject><subject>Search algorithms</subject><subject>Synthesis</subject><subject>X-band</subject><issn>0895-2477</issn><issn>1098-2760</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><recordid>eNqN0U9v0zAYBnALgUQZHPgGlrjAIZv_JY6PbNrWibKhDQQ3y3betG4Tu9jJRr_9UgockJA4WXr1e17p9YPQa0qOKSHspI_bY6a4UE_QjBJVF0xW5CmakVqVBRNSPkcvcl4TQriUbIaGUx99yFufoMH92A0-2jW4wd8DzrswrCD7jGOLvxXWhAZf3N3he2_wEgIk0-EEywQ5-xhwgHE_CTA8xLTBe-1Gt4kRZzDJrbDpljH5YdW_RM9a02V49es9Ql8uzj-fzYvFzeXV2ftF4QShqqiA1qxR0lpg1pRMuIq7lgDjvFGCGG7b2tUgZEsaS2pjqobxsgELjrZWKX6E3h72blP8PkIedO-zg64zAeKY9bSeK0GJ-A8qaa1ERWg10Td_0XUcU5gO0bRSqpy-lrBJvTsol2LOCVq9Tb43aacp0fuq9FSV_lnVZE8O9sF3sPs31B9vPv1OFIeEzwP8-JMwaaMryWWpv15f6tu5_LC4vZ7rU_4IgsmmWA</recordid><startdate>201510</startdate><enddate>201510</enddate><creator>Neto, M. 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Alcantara</au><au>Araújo, J. P. L.</au><au>Barros, F. J. B.</au><au>Silva, A. N.</au><au>Cavalcante, G. P. S.</au><au>D'Assunção, A. G.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Bioinspired multiobjective synthesis of X-band FSS via general regression neural network and cuckoo search algorithm</atitle><jtitle>Microwave and optical technology letters</jtitle><addtitle>Microw. Opt. Technol. Lett</addtitle><date>2015-10</date><risdate>2015</risdate><volume>57</volume><issue>10</issue><spage>2400</spage><epage>2405</epage><pages>2400-2405</pages><issn>0895-2477</issn><eissn>1098-2760</eissn><coden>MOTLEO</coden><abstract>ABSTRACT
A bioinspired hybrid multiobjective optimization technique that associates a general regression neural network and a cuckoo search algorithm is proposed for microwave applications. This study is focused on the simulation, design, and synthesis of frequency selective surfaces (FSSs) with triangular ring patch elements printed on fiberglass substrates (FR4). The proposed technique aims, for example, to design FSSs with specific values for the resonance frequency and bandwidth in the frequency range from 8 to 12 GHz. For validation purpose, a bandstop FSS filter, centered at 11 GHz and with a 4 GHz bandwidth, was synthesized, fabricated, and measured. Good agreement between simulated and measured results is reported. © 2015 Wiley Periodicals, Inc. Microwave Opt Technol Lett 57:2400–2405, 2015</abstract><cop>New York</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1002/mop.29349</doi><tpages>6</tpages></addata></record> |
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| subjects | Bandwidth bioinspired computing Computer simulation frequency selective surface general regression neural network General regression neural networks Microwaves multiobjective cuckoo search Optimization Search algorithms Synthesis X-band |
| title | Bioinspired multiobjective synthesis of X-band FSS via general regression neural network and cuckoo search algorithm |
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