Application of Artificial Neural Networks for Modeling of the Frequency-Dependent Performance of Surface Acoustic Wave Resonators-Reference-Cited by-同舟云学术

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Application of Artificial Neural Networks for Modeling of the Frequency-Dependent Performance of Surface Acoustic Wave Resonators

Published:2021-06-16 Issue: Volume: Page:
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Container-title:2021 56th International Scientific Conference on Information, Communication and Energy Systems and Technologies (ICEST)
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Author:

Marinkovic Zlatica,Gugliandolo Giovanni,Campobello Giuseppe,Crupi Giovanni,Donato Nicola

Funder

Serbian Ministry for Education, Science and Technological Development

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9482411/9483448/09483548.pdf?arnumber=9483548

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Machine-Learning-Based Method to Accelerate the Design of SAW Filters at Different Frequency Bands;IEEE Sensors Journal;2024-08-15

2. The Design of SAW Filters With CNN Modeling and Cuckoo Search (CS) Optimization;2024 IEEE MTT-S International Conference on Microwave Acoustics & Mechanics (IC-MAM);2024-05-13

3. Development and Validation of an ANN-Based Approach for Temperature-Dependent Equivalent Circuit Modeling of SAW Resonators;Micromachines;2023-04-28

4. Finite Element Analysis Model of Electronic Skin Based on Surface Acoustic Wave Sensor;Nanomaterials;2023-01-23

5. A Combined Approach Using Lorentzian Fitting and ANNs for Microwave Resonator Modeling;2022 IEEE International Conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE);2022-10-26

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