71 / 2023-08-31 22:52:56
A Prior Knowledge-Based Neural Network Model for Degradation Prediction of Microwave HBT S-parameters
S-parameters,degradation,prior knowledge,extreme learning machine
终稿
Hongliang Lv / Xidian University
Lin Cheng / Xidian University
Silu Yan / Xidian University
Junjun Qi / Xidian University
Wei Cheng / Nanjing Electronic Devices Institute
Yuming Zhang / Xidian University
In this paper, a prior knowledge neural network (PKNN)-based modeling approach for degradation prediction of microwave HBT S-parameters is explored. In addition to the reliability parametric inputs of the original aging problem, the Sparameter degradation trend obtained from the aging small-signal equivalent circuit is used as an additional information to inject into the extreme learning machine structure. Good agreement was achieved between measured and predicted results of the degradation of S-parameters within a frequency range of 0.1 to 40 GHz.

 
重要日期
  • 会议日期

    11月02日

    2023

    11月04日

    2023

  • 12月15日 2023

    初稿截稿日期

  • 12月20日 2023

    注册截止日期

主办单位
IEEE Instrumentation and Measurement Society
Xidian University
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