Prior Knowledge Input Method In Device Modeling

The artificial neural networks are being used in modelling electronic elements and devices especially at microwave frequencies where non-linearity and dependence on frequency cannot be neglected. In this paper, instead of using artificial neural networks as a unique modelling device prior knowledge input method based on feed-forward artificial neural network structures as multi-layer perceptrons and wavelet-based neural networks is investigated. The benefits of prior knowledge input method over plain usage of artificial neural networks in modelling BJT is explored by comparing models obtained with and without prior knowledge input. The novelty of the paper is utilizing wavelet-based neural networks as feed-forward structure in prior knowledge input method. The training and test data used in simulations are obtained by HP 4155 parameter analyser.

Prior Knowledge Input Method In Device Modeling

The artificial neural networks are being used in modelling electronic elements and devices especially at microwave frequencies where non-linearity and dependence on frequency cannot be neglected. In this paper, instead of using artificial neural networks as a unique modelling device prior knowledge input method based on feed-forward artificial neural network structures as multi-layer perceptrons and wavelet-based neural networks is investigated. The benefits of prior knowledge input method over plain usage of artificial neural networks in modelling BJT is explored by comparing models obtained with and without prior knowledge input. The novelty of the paper is utilizing wavelet-based neural networks as feed-forward structure in prior knowledge input method. The training and test data used in simulations are obtained by HP 4155 parameter analyser.

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  • Q.J. Zhang, K.C. Gupta, Neural Networks for RF and Microwave Design , Arctech House, 2000.
  • Bakr Muhammed H., Bandler John W., Madsen Kaj, Sondergaard Jacob, “Review of The Space Mapping Approach to Engineering Optimisation and Modelling”, http://www.sos.mcmaster.ca
  • F. Wang, Q.J. Zhang, Knowledge-Based Neural Models for Microwave Design, IEEE Trans. on Microwave Theory and Techniques, Vol. 45, No.12, December 1997.
  • L. Chao, X. Jun, X. Liangjin, Knowledge-Based Artificial Neural Network Models for Finline, International Journal of Infrared and Millimeter Waves, Vol. 22, No. 2, 2001
  • P.M. Watson, K.C. Gupta, R.L. Mahajan, Applications of Knowledge-Based Artificial Neural Network Modeling to Microwave Components, Int. J. RF and Microwave CAE, 9:254-260, 1999.
  • Q. Zhang, Using Wavelet Network in Nonparametric Estimation, IEEE Trans. On Neural Networks, Vol.8, No. 2, march 1997.
  • S. Haykin, Neural Networks: A Comprehensive Foundation, Prentice Hall, 1999.