Please use this identifier to cite or link to this item:
https://hdl.handle.net/11499/6217| Title: | Neural network applications for optimization of microstrip linear phase filter with inset feeding | Authors: | Karpuz, Ceyhun Özek, Ahmet Görür, A. Ba?, N. Öztürk, P. |
Keywords: | Application area Artificial Neural Network Filter designs Geometrical dimensions Input-output Inset feeding Linear phase Linear phase filters Microstripes Microwave structures Modeling technique Neural network application Open-loop resonators Simulation result Solution techniques Computer simulation Electrical engineering Microstrip filters Neural networks Optimization Signal filtering and prediction Microwave filters |
Abstract: | ANN has a wide application areas. One of these applications areas is the optimization of microwave filters. In this study, of optimization ANN solution techniques have been applied to optimize RF and microwave structures Using Artificial neural networks (ANN) modeling technique in a filter design with the inset-feeding open-loop resonator is presented. With helping the Sonnet EM Simulator, to develop a new ANN model, the datas was produced. The modeling techniques which is in the Neuro Solutions Program were used for this process. The geometrical dimension of filter and coupling gap can be used to determine input output(I/O) relations of ANN model. As a result, for the -linear phase- microstrip filter, the results , which was obtained from the ANN model were compared with the experiment and simulation result. And provided a good agreement was observed. | URI: | https://hdl.handle.net/11499/6217 | ISBN: | 9781424495887 |
| Appears in Collections: | Mühendislik Fakültesi Koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection |
Show full item record
CORE Recommender
Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.