Title :
A neural network approach to smooth calibrated data corrupted from switching errors
Author :
Landa, A.Z. ; Pulido-Gaytan, M.A. ; Reynoso-Hernandez, J.A. ; Roblin, Patrick ; Loo-Yau, J.R.
Author_Institution :
Centro de Investig. Cienc. y de Educ. Super. de Ensenada (CICESE), Ensenada, Mexico
Abstract :
A reliable calibration of the vector network analyzer is needed in order to characterize microwave devices. For some VNAs, such as HP8510, solving the 8 error model is not enough to accurately compute the device under test (DUT) S-parameters, but also, a correction of the switching errors inherent to the measurement must be performed. In this paper, a neural network is used to find the S-parameters of the DUT free from switching errors instead of calculating the well-known equations used for that matter.
Keywords :
S-parameters; calibration; computerised instrumentation; microwave devices; network analysers; neural nets; DUT S-parameters; HP8510; VNA; device under test S-parameters; microwave devices; neural network approach; smooth calibrated data; switching error correction; vector network analyzer; Artificial neural networks; Calibration; Measurement uncertainty; Neurons; Scattering parameters; Switches; Training; Vector network analyzer (VNA) calibration; artificial neural networks (ANN); switching errors;
Conference_Titel :
Microwave Measurement Symposium (ARFTG), 2012 80th ARFTG
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4673-4817-1
Electronic_ISBN :
978-1-4673-4820-1
DOI :
10.1109/ARFTG.2012.6422428
