Signal-noise support vector model of a microwave transistor

Guenes F., Tuerker N., Guergen F.

INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING, vol.17, no.4, pp.404-415, 2007 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 17 Issue: 4
  • Publication Date: 2007
  • Doi Number: 10.1002/mmce.20239
  • Journal Name: INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.404-415
  • Keywords: support vectors, artificial neural networks, generalization, global optimization, microwave transistor, scattering parameters, noise parameters, NEURAL-NETWORK MODEL, DEVICES
  • Yıldız Technical University Affiliated: Yes

Abstract

In this work, a support vector machines (SVM) model for the small-signal and noise behaviors of a microwave transistor is presented and compared with its artificial neural network (ANN) model. Convex optimization and generalization properties of SVM are applied to the black-box modeling of a microwave transistor. It has been shown that SVM has a high potential of accurate and efficient device modeling. This is verified by giving a worked example as compared with ANN which is another commonly used modeling technique. It can be concluded that hereafter SVM modeling is a strongly competitive approach against ANN modeling.