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Artificial Neural Network Models for the Double-Vias in Multilayer Stripline Circuits

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Abstract

Multi-vias is a kind of interconnection largely existing in the multi-chip module (MCM) packages for high-speed digital circuits. In this paper, a multilayer perceptron neural network (MLPNN) is used to model the double-vias in multilayer stripline circuits. The MLPNN is electromagnetically developed with a set of training data that are produced by the full-wave finite-difference time-domain (FDTD) method. One type of the designs of experiments, the central composite technique, is used to allow for a minimum number of FDTD simulations that is needed to be performed.

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Authors and Affiliations

  1. Research Institute of Applied Physics, University of Electronic Science and Technology of China, Chengdu, 610054, Peoples Republic of China

    Bing-Zhong Wang & Shaoyun Zou

Authors
  1. Bing-Zhong Wang
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  2. Shaoyun Zou
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Wang, BZ., Zou, S. Artificial Neural Network Models for the Double-Vias in Multilayer Stripline Circuits. International Journal of Infrared and Millimeter Waves 20, 1377–1387 (1999). https://doi.org/10.1023/A:1021731013085

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  • DOI: https://doi.org/10.1023/A:1021731013085

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