✦ LIBER ✦

Improved measurement of complex permittivity using artificial neural networks with scaled inputs

✍ Scribed by Azhar Hasan; Andrew F. Peterson

Publisher: John Wiley and Sons
Year: 2011
Tongue: English
Weight: 363 KB
Volume: 53
Category: Article
ISSN: 0895-2477
DOI: 10.1002/mop.26221

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✦ Synopsis

Abstract

A procedure is described to enhance the accuracy of microwave measurements of the complex permittivity of a dissipative medium.Monopole probe measurements are used in conjunction with two real‐valued neural networks, which are integrated together to reconstruct the complex permittivity from the measured reflection coefficients. The approach is tested over the frequency range from 2.5 to 5 GHz, for the real part of the permittivity in the range 3–10 and the imaginary part in the range 0– 0.5. The performance of the network is also demonstrated for a reduced frequency range from 3.5 to 5 GHz. Less than 4% error was observed in the presence of white Gaussian noise with an SNR of 10dB. © 2011 Wiley Periodicals, Inc. Microwave Opt Technol Lett, 2011; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.26221

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