EM-based optimization of microwave circuits using artificial neural networks: the state-of-the-art
By José Ernesto Rayas-Sánchez. IEEE transactions on microwave theory and techniques, 2003
395 citations recorded by the source corpus.
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.
Subfields: Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/33b752fab7e88e1d945df233b292dee8829435c8
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In Electrical and Electronic Engineering
Citations in the corpus
- Space mapping: the state of the art (2004, background): “Bakr [25] introduces advances in SM algorithms, Rayas-Sánchez [26] employs ANNs, and Ismail [27] studies SM-based model enhancement.”