Consensus Deep Neural Networks for Antenna Design and Optimization

We present a general approach for antenna design and optimization based on consensus of results from a number of independently trained deep neural networks (DNNs). The aim of using the consensus is to reduce the uncertainty of results from a single DNN. The approach leads to several orders of magnit...

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Veröffentlicht in:	IEEE transactions on antennas and propagation 2022-07, Vol.70 (7), p.5015-5023
Hauptverfasser:	Stankovic, Zoran Z., Olcan, Dragan I., Doncov, Nebojsa S., Kolundzija, Branko M.
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive arrays Antenna arrays Antenna design Antennas Artificial neural networks Artificial neural networks (ANNs) Design optimization Design parameters Method of moments Multilayer perceptrons multilayer perceptrons (MLP) Optimization Optimized production technology Testing Training Yagi antennas Yagi–Uda antennas
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