The recent developments in microwave design

Murat Simsek, Qi Jun Zhang*, Humayun Kabir, Yazi Cao, Neslihan Serap Sengor

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)

Abstract

Artificial neural networks have been used as an important technique in microwave modelling and optimisation. This paper gives an overview and recent developments on the knowledge-based neural modelling techniques in microwave modelling and design. The knowledge-based artificial neural networks are constructed by incorporating the existing knowledge such as empirical formulas, equivalent circuit models and semi-analytical equations in neural network structures. When one of the knowledge-based methods can not provide sufficient accuracy, two of them can be used in the same modelling process. This combination of methods is named hybrid technique. Using knowledge-based techniques requires less training data and has better extrapolation performance than classical neural networks. The advantages of using knowledge-based neural network modelling are demonstrated with microwave device modelling applications.

Original languageEnglish
Pages (from-to)213-228
Number of pages16
JournalInternational Journal of Mathematical Modelling and Numerical Optimisation
Volume2
Issue number2
DOIs
Publication statusPublished - Apr 2011

Keywords

  • Computer-aided design
  • KBNN
  • Knowledge-based neural networks
  • Mathematical modelling
  • Microwave devices

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