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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-
Γλώσσαen-
Μέγεθος6 pagesen
ΤίτλοςComputational investigation of asymmetric coplanar waveguides using neural networks: A microwave engineering exerciseen
ΔημιουργόςLiodakis Georgiosen
ΔημιουργόςΛιοδακης Γεωργιοςel
Δημιουργός I.O. Vardiambasisen
ΔημιουργόςK. Karamichalisen
ΕκδότηςWorld Scientific and Engineering Academy and Societyen
ΠερίληψηIn 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
ΤύποςΠλήρης Δημοσίευση σε Συνέδριοel
ΤύποςConference Full Paperen
Άδεια Χρήσηςhttp://creativecommons.org/licenses/by/4.0/en
Ημερομηνία2015-10-29-
Ημερομηνία Δημοσίευσης2005-
Θεματική ΚατηγορίαProduct line engineering, Softwareen
Θεματική Κατηγορίαsoftware product line engineeringen
Θεματική Κατηγορίαproduct line engineering softwareen
Βιβλιογραφική ΑναφοράK. 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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