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Publication Citation: Artificial Neural Network Modeling for Improved On-Wafer Line-Reflect-Match Calibrations

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Author(s): Jeffrey A. Jargon; Kuldip Gupta;
Title: Artificial Neural Network Modeling for Improved On-Wafer Line-Reflect-Match Calibrations
Published: September 01, 2001
Abstract: We model a load using an artificial neural network (ANN) to improve an on-wafer line-reflect-match (LRM) calibration of a vector network analyzer. The ANN is trained with measurement data obtained from a thru-reflect-line (TRL) calibration. The accuracy of the LRM calibration using the ANN-modeled load compares favorably to a benchmark multiline TRL calibration with an average worst-case scattering parameter error bound of 0.017 over a 40 GHz bandwidth.
Conference: European Microwave Conference
Pages: pp. 229 - 232
Location: London, UK
Dates: September 24-28, 2001
Keywords: artificial neural network;calibration;line-refelct-match;network analyzer;
Research Areas: Microwave Measurement Services