A vector approach for noise parameter fitting and selection of source admittances

Abstract
Simple vector concepts can be used in the determination of noise parameters from measured data. The use of such concepts leads to a simplification in the least-square fitting algorithm, complete determination of the admittance loci that produce ill conditioning, and simple criteria for the selection of source admittances that minimize the sensitivity of the noise parameters to experimental error. The sensitivity of the noise parameters to small perturbations in the reflection coefficients is compared for a group of source admittances presented in previous work. The results show that a great reduction in the error of the noise parameters can be achieved by properly selecting the source admittancesPeer ReviewedPostprint (published version

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