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Efficient Sensitivity Analysis of Dynamic Neuro-space Mapping for Transistor Modeling

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Communications, Signal Processing, and Systems (CSPS 2018)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 517))

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Abstract

In this paper, an enhanced dynamic Neuro-space mapping (Neuro-SM) method is proposed with emphasis on transistor modeling. By modifying the dynamic voltage relationships in an existing nonlinear model, the proposed Neuro-SM produces a new and more accurate model than the nonlinear model as well as the static Neuro-SM. Compared to the existing dynamic Neuro-SM, a new sensitivity analysis technique is derived to speed up the training of the proposed model with dc, small- and large-signal data. The validity and efficiency of the proposed Neuro-SM method are demonstrated by modeling examples of a GaAs high-electron-mobility transistor (HEMT). Suitable value of time delay parameter which is equal to one divided by 3 or 5 times of the largest frequency considered in simulation is suggested and demonstrated by the modeling example.

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References

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Acknowledgements

This work is supported by Scientific Research Plan Project by Tianjin Education Commission (No. 2016CJ13).

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Authors and Affiliations

  1. Tianjin Chengjian University, Tianjin, China

    Lin Zhu & Jian Zhao

  2. Shaanxi University of Science and Technology, Xi’an, China

    Wenyuan Liu

Authors
  1. Lin Zhu
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  2. Jian Zhao
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  3. Wenyuan Liu
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Corresponding author

Correspondence to Lin Zhu .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, University of Texas at Arlington, Arlington, TX, USA

    Qilian Liang

  2. School of Information and Communication Engineering, Dalian University of Technology, Dalian, China

    Xin Liu

  3. School of Information Science and Technology, Dalian Maritime University, Dalian, China

    Zhenyu Na

  4. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Wei Wang

  5. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Jiasong Mu

  6. College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin, China

    Baoju Zhang

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Zhu, L., Zhao, J., Liu, W. (2020). Efficient Sensitivity Analysis of Dynamic Neuro-space Mapping for Transistor Modeling. In: Liang, Q., Liu, X., Na, Z., Wang, W., Mu, J., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2018. Lecture Notes in Electrical Engineering, vol 517. Springer, Singapore. https://doi.org/10.1007/978-981-13-6508-9_69

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  • DOI: https://doi.org/10.1007/978-981-13-6508-9_69

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-6507-2

  • Online ISBN: 978-981-13-6508-9

  • eBook Packages: EngineeringEngineering (R0)

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