Multilaver perceptron neural networks to compute quasistatic parameters of asymmetric coplanar waveguides

Ubeyli E., Guler İ.

NEUROCOMPUTING, cilt.62, ss.349-365, 2004 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 62
  • Basım Tarihi: 2004
  • Doi Numarası: 10.1016/j.neucom.2004.04.005
  • Dergi Adı: NEUROCOMPUTING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.349-365
  • Anahtar Kelimeler: asymmetric coplanar waveguides, quasistatic parameters, conformal mapping, artificial neural networks, multilayer perceptron, training algorithms, Levenberg-Marquardt algorithm, DESIGN INVITED ARTICLE, ALGORITHMS, COMPONENTS, MODELS, LINES
  • Gazi Üniversitesi Adresli: Evet

Özet

Artificial neural networks (ANNs) have recently gained attention as fast and flexible vehicles to microwave modeling, simulation, and optimization. In this study, ANNs, based on the multilayer perceptron, were presented for accurate computation of the quasistatic parameters of asymmetric coplanar waveguides (ACPWs). Multilayer perceptron neural networks (MLPNNs) were trained with backpropagation, delta-bar-delta, extended delta-bar-delta, quick propagation, and Levenberg-Marquardt algorithms to compute the quasistatic parameters, the characteristic impedance and the effective dielectric constant, of the ACPWs. The results of the MLPNNs trained with the Levenberg-Marquardt algorithm for the quasistatic parameters of the ACPWs were in very good agreement with the results available in the literature obtained by using conformal-mapping technique. (C) 2004 Elsevier B.V. All rights reserved.