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Development and validation of ANN approach for extraction of MESFET/HEMT noise model parameters

Electrical Engineering volume 100, pages 645–651 (2018)Cite this article

Abstract

Most of the transistor noise models refer to the intrinsic device, providing relationships between the transistor noise model parameters and the noise parameters of the intrinsic device. Having in mind that the measured noise parameters correspond to the whole device including the device parasitics, the parameters of the noise models are most often determined by using optimizations in circuit simulators. In this paper, an efficient neural approach for straightforward determination of the noise model parameters, avoiding optimizations, is proposed. A detailed validation of the proposed approach was done by comparison of the measured transistor noise parameters with those obtained by using the extracted noise model parameters for two noise models—the Pospieszalski’s noise model and the noise wave model.

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Acknowledgements

The work was supported by the TR-32052 Project of the Serbian Ministry of Education, Science and Technological Development. The authors would like to thank prof. Alina Caddemi, University of Messina, Italy, for providing the measured data.

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Authors and Affiliations

  1. Innovation Centre of Advanced Technologies, Bulevar Nikole Tesle 61, lokal 5, Niš, 18000, Serbia

    Vladica Ɖorđević

  2. Faculty of Electronic Engineering, University of Niš, Aleksandra Medvedeva 14, Niš, 18000, Serbia

    Zlatica Marinković, Vera Marković & Olivera Pronić-Rančić

Authors
  1. Vladica Ɖorđević
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  2. Zlatica Marinković
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  3. Vera Marković
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  4. Olivera Pronić-Rančić
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Correspondence to Vladica Ɖorđević.

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Ɖorđević, V., Marinković, Z., Marković, V. et al. Development and validation of ANN approach for extraction of MESFET/HEMT noise model parameters. Electr Eng 100, 645–651 (2018). https://doi.org/10.1007/s00202-017-0526-2

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  • DOI: https://doi.org/10.1007/s00202-017-0526-2

Keywords

  • Artificial neural network
  • HEMT
  • MESFET
  • Noise parameters
  • Noise wave model
  • Pospieszalski’s noise model