论文信息 - Artificial Neural Network Models for the Gap Discontinuities in Stripline Circuits

Artificial Neural Network Models for the Gap Discontinuities in Stripline Circuits

Gap discontinuities 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 gap 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 (FDTD) method. The full-factor design of experiments is used for determining the size of the training data.

Jing-Song Hong | Bing-Zhong Wang

[1] N.G. Alexopoulos,et al. Microstrip circuit design using neural networks , 1993, 1993 IEEE MTT-S International Microwave Symposium Digest.

[2] G. L. Creech,et al. Artificial neural networks for fast and accurate EM-CAD of microwave circuits , 1997 .

[3] Simon Haykin,et al. Neural Networks: A Comprehensive Foundation , 1998 .

[4] Michel Nakhla,et al. The application of neural networks to EM-based simulation and optimization of interconnects in high-speed VLSI circuits , 1997 .

[5] S. R. Schmidt,et al. Understanding industrial designed experiments , 1992 .

[6] K. C. Gupta,et al. EM-ANN models for microstrip vias and interconnects in dataset circuits , 1996 .