Complex permittivity reconstruction with neural networks
PublicThis project deals with an original method of determination of dielectric properties of materials, based minimally on measurements and heavily on modeling. Complex permittivity is reconstructed by a neural networking procedure matching measured and modeled characteristics of reflection coefficient. The experimental part of the method is implemented on the basis of a rectangular waveguide suitable for acquiring dielectric properties at 915 MHz. Full operation of the method is demonstrated through its validation and determination of complex permittivity of liquid substances (fresh and saline water, milk). Experimental and computational studies reveal important features of the current implementation and generate recommendations regarding its further development.
- This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.
- Creator
- Publisher
- Identifier
- 03D159M
- Advisor
- Year
- 2003
- Sponsor
- Date created
- 2003-01-01
- Resource type
- Major
- Rights statement
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