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Computational investigation of asymmetric coplanar waveguides using neural networks: A microwave engineering exercise

Liodakis Georgios, I.O. Vardiambasis, K. Karamichalis

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URIhttp://purl.tuc.gr/dl/dias/F0C1568C-CCD9-48AB-8F70-AD696E5DF5CD-
Languageen-
Extent6 pagesen
TitleComputational investigation of asymmetric coplanar waveguides using neural networks: A microwave engineering exerciseen
CreatorLiodakis Georgiosen
CreatorΛιοδακης Γεωργιοςel
Creator I.O. Vardiambasisen
CreatorK. Karamichalisen
PublisherWorld Scientific and Engineering Academy and Societyen
Content SummaryIn order to compute the characteristic impedance and the relative effective dielectric constant of an asymmetric coplanar waveguide with infinite or finite dielectric thickness, the use of artificial neural networks is valuable. The method of neural computing presented in this paper uses only one neural model for both parameters, for this specific waveguide type. The BFGS quasi-Newton back-propagation algorithm was used to train the developed neural network. Numerical results are given for several configurations along with comparisons with previously published dataen
Type of ItemΠλήρης Δημοσίευση σε Συνέδριοel
Type of ItemConference Full Paperen
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2015-10-29-
Date of Publication2005-
SubjectProduct line engineering, Softwareen
Subjectsoftware product line engineeringen
Subjectproduct line engineering softwareen
Bibliographic CitationK. Karamichalis, I.O. Vardiambasis, and G. Liodakis, "Computational investigation of asymmetric coplanar waveguides using neural networks: A microwave engineering exercise," in Proc. of the 2005 WSEAS Inter. Con. on Engin. Edu. (EE'05), July, pp. 8-10.en

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