Artificial neural networks for RF and microwave design - from theory to practice
By Qi-jun Zhang, V. Devabhaktuni, K. Gupta. 2003
712 citations recorded by the source corpus.
Subfields: Electrical and Electronic Engineering, Environmental Engineering
View Paper: https://www.semanticscholar.org/paper/0d231badc8f8aa5321f21b919dff2c116629917c
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In Electrical and Electronic Engineering
Citations in the corpus
- Artificial Intelligence Aided Automated Design for Reliability of Power Electronic Systems (2019, neutral): “Forward ANNs are the most commonly used deep-learning algorithms and have been applied already to various electrical engineering problems, from predicting the voltage distortion in electrical distribution networks [28], to designing the microwave filters [29], [30].”
- Weighting Factor Design in Model Predictive Control of Power Electronic Converters: An Artificial Neural Network Approach (2019, background): “learning algorithms for various electrical engineering problems, from predicting the voltage distortion in electrical distribution networks [26], to designing the microwave filters [27], [28].”
- Neural Network Inverse Modeling and Applications to Microwave Filter Design (2008, background): “In this way, more training time is needed only with more complexity in the model IO relationship, such as the multivalued relationship.”