Machine learning approach to transform scattering parameters to complex permittivities-Reference-Cited by-同舟云学术

Machine learning approach to transform scattering parameters to complex permittivities

Published:2021-10-02 Issue:4 Volume:55 Page:287-302
ISSN:0832-7823
Container-title:Journal of Microwave Power and Electromagnetic Energy
language:en
Short-container-title:Journal of Microwave Power and Electromagnetic Energy

Author:

Tempke Robert¹²,Thomas Liam¹,Wildfire Christina³,Shekhawat Dushyant³,Musho Terence¹^ORCID

Affiliation:

1. Department of Mechanical & Aerospace Engineering, West Virginia University, Morgantown, WV, USA

2. Oak Ridge Institute of Science and Education (ORISE), Oak Ridge, TN, USA

3. National Energy Technology Laboratory, US Department of Energy, Morgantown, WV, USA

Funder

NSF

Publisher

Informa UK Limited

Subject

Electrical and Electronic Engineering,Metals and Alloys,Condensed Matter Physics,Ceramics and Composites,Electronic, Optical and Magnetic Materials

Link

https://www.tandfonline.com/doi/pdf/10.1080/08327823.2021.1993046

Reference32 articles.

1. Baker-Jarvis J, Janezic MD, Grosvenor JH, Jr., Geyer RG. 1992. Transmission/reflection and short-circuit line methods for measuring permittivity and permeability. Washington, DC: NIST.

2. A new technique for the determination of the complex permittivity and permeability of materials

3. Comments on "Automatic measurement of complex dielectric constant and permeability at microwave frequencies"

4. Comments on "Automatic measurement of complex dielectric constant and permeability at microwave frequencies"

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