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Artificial Neural Network Models for the Crossover Discontinuities in Stripline Circuits

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Abstract

Crossover discontinuities between two adjacent orthogonal signal layers often appear in many stripline circuits, such as the multilayer microwave monolithic ICs and the interconnect systems in high-speed digital circuits. In this paper , a multilayer perceptron neural network(MLPNN) is used to model the electrical properties of the crossover discontinuities in stripline circuits. The MLPNN is electromagnetically developed with a set of training data that are produced by the full-wave finite-difference time-domain method. The full-factor design of experiments is used to determine the size of the training data.

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Authors and Affiliations

  1. Institute of Applied Physics, University of Electronic Science and Technology of China, Chengdu, 610054, People's Republic of China

    Jingsong Hong & Bing-Zhong Wang

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  1. Jingsong Hong
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  2. Bing-Zhong Wang
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Hong, J., Wang, BZ. Artificial Neural Network Models for the Crossover Discontinuities in Stripline Circuits. International Journal of Infrared and Millimeter Waves 20, 1939–1956 (1999). https://doi.org/10.1023/A:1022989332445

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