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dc.contributor.authorYang, Shuai
dc.contributor.authorKhusro, Ahmad
dc.contributor.authorLi, Weiwei
dc.contributor.authorVaseem, Mohammad
dc.contributor.authorHashmi, Mohammad
dc.contributor.authorShamim, Atif
dc.date.accessioned2021-12-01T11:47:53Z
dc.date.available2021-12-01T11:47:53Z
dc.date.issued2021-11-30
dc.date.submitted2021-05-07
dc.identifier.citationYang, S., Khusro, A., Li, W., Vaseem, M., Hashmi, M., & Shamim, A. (2021). Optimization of ANN -based models and its EM co-simulation for printed RF devices. International Journal of RF and Microwave Computer-Aided Engineering. doi:10.1002/mmce.23012
dc.identifier.issn1096-4290
dc.identifier.issn1099-047X
dc.identifier.doi10.1002/mmce.23012
dc.identifier.urihttp://hdl.handle.net/10754/673868
dc.description.abstractPrinted VO2 RF switch founds immense potential in RF reconfigurable applications. However, their generic electrical equivalent model is still intangible that can be further integrated in CAD tools and utilize for simulation, analysis and design of RF/microwave circuits and systems. The artificial neural network (ANN) has been gaining popularity in modeling various types of RF components. However, most of these works merely demonstrate the establishment of the ANN-based RF model in the MATLAB environment without involving significant optimization. Furthermore, the integration of such ANN-based RF models in the EM and circuit simulator as well as the co-simulation between the ANN-based model and conventional models have not been demonstrated or validated. Therefore, the earlier reported models are still one step removed from its real RF applications. In this work, by using the fully printed vanadium dioxide (VO2) RF switch as the modeling example, a systematic hyperparameter optimization process has been conducted. Compared to the non-optimized ANN model, a dramatic improvement in the model's accuracy has been observed for the ANN model with fully optimized hyperparameters. A correlation coefficient of more than 99.2% for broad frequency range demonstrates the accuracy of the modeling technique. In addition, we have also integrated the Python-backed ANN-based model into Advanced Design System (ADS), where a reconfigurable T-resonator band stop filter is used as an example to demonstrate the co-simulation between the ANN-based model and the conventional lumped-based model.
dc.publisherWiley
dc.relation.urlhttps://onlinelibrary.wiley.com/doi/10.1002/mmce.23012
dc.rightsArchived with thanks to International Journal of RF and Microwave Computer-Aided Engineering
dc.titleOptimization of ANN -based models and its EM co-simulation for printed RF devices
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Science and Engineering (CEMSE) Division
dc.contributor.departmentElectrical and Computer Engineering Program
dc.contributor.departmentIntegrated Microwave Packaging Antennas and Circuits Technology (IMPACT) Lab
dc.identifier.journalInternational Journal of RF and Microwave Computer-Aided Engineering
dc.rights.embargodate2022-11-30
dc.eprint.versionPost-print
dc.contributor.institutionElectrical Engineering Department Jamia Millia Islamia New Delhi India
dc.contributor.institutionSchool of Engineering and Digital Sciences (SEDS) Nazarbayev University Nur-Sultan Kazakhstan
kaust.personYang, Shuai
kaust.personLi, Weiwei
kaust.personVaseem, Mohammad
kaust.personShamim, Atif
dc.date.accepted2021-11-18
dc.date.published-online2021-11-30
dc.date.published-print2022-03


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