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
Citations
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Journal ArticleDOI
Automated Knowledge-Based Neural Network Modeling for Microwave Applications
Weicong Na,Qi-Jun Zhang +1 more
TL;DR: The proposed method automates data generation, determination of data distribution, model structure adaptation, and model training in a systematic framework, and can further reduce the number of training data through the adaptive sampling process, shorten the model development time over existing AMG methods and existing knowledge-based modeling methods.
Journal ArticleDOI
Modeling and design of printed antennas using neural networks
TL;DR: In this article, a single neural network is developed to model the resonant frequency of rectangular patch printed on uniaxially anisotropic substrate with air gap using effective parameters in conjunction with spectral dyadic Green's function.
Journal ArticleDOI
Parallel Computational Approach to Gradient Based EM Optimization of Passive Microwave Circuits
TL;DR: This work proposes to use a large number of fine model evaluations to achieve an overall speedup of gradient based EM optimization when no coarse model is available, thereby resulting in fewer iterations of the optimization process.
Journal ArticleDOI
Multifeature-Assisted Neuro-transfer Function Surrogate-Based EM Optimization Exploiting Trust-Region Algorithms for Microwave Filter Design
TL;DR: The pole–zero-based neuro-TF is introduced in this article to help extract the multiple feature parameters when the feature parameters of filter responses are not explicitly identified.
Journal ArticleDOI
ANNs for Fast Parameterized EM Modeling: The State of the Art in Machine Learning for Design Automation of Passive Microwave Structures
TL;DR: Artificial neural networks (ANNs) are information processing systems, with their design inspired by studies of the ability of the human brain to learn from observations and generalize by abstraction as discussed by the authors.
References
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