Journal ArticleDOI
EM-based optimization of microwave circuits using artificial neural networks: the state-of-the-art
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Abstract:
This paper reviews the current state-of-the-art in electromagnetic (EM)-based design and optimization of microwave circuits using artificial neural networks (ANNs). Measurement-based design of microwave circuits using ANNs is also reviewed. The conventional microwave neural optimization approach is surveyed, along with typical enhancing techniques, such as segmentation, decomposition, hierarchy, design of experiments, and clusterization. Innovative strategies for ANN-based design exploiting microwave knowledge are reviewed, including neural space-mapping methods. The problem of developing synthesis neural networks is treated. EM-based statistical analysis and yield optimization using neural networks is reviewed. The key issues in transient EM-based design using neural networks are summarized. The use of ANNs to speed up "global modeling" for EM-based design of monolithic microwave integrated circuits is briefly described. Future directions in ANN techniques to microwave design are suggested.read more
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Journal ArticleDOI
Fast Synthesis Method for High-Dimensional Electromagnetic Bandgap Structure Using Deep Neural Network for Power/Ground Noise Suppression
Seong-Soo Sim,Myung-Duk Kim +1 more
TL;DR: In this article , a deep neural network (DNN)-based method is proposed for the fast synthesis of a high-dimensional electromagnetic bandgap structure (HD-EBG) suppressing the power/ground noise in high-speed packages and printed circuit boards (PCBs).
References
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Journal ArticleDOI
Optimal Global Rates of Convergence for Nonparametric Regression
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