Publication | Closed Access
Error bounds analysis of de-embedded results in 2x thru de-embedding methods
30
Citations
7
References
2017
Year
Unknown Venue
Numerical AnalysisSparse RepresentationEngineeringManifold LearningSmart Fixture De-embeddingDe-embedded ResultsLower BoundComputer EngineeringMultilinear Subspace LearningInverse ProblemsComputer ScienceComputational ElectromagneticsUpper BoundDimensionality ReductionComputational GeometryThru De-embedding MethodsSignal ProcessingLow-rank Approximation
In this paper, an error bound analysis is performed for 2x thru de-embedding methods: AFR (Automatic Fixture Removal) and SFD (Smart Fixture De-embedding). Basically, a certain amount of error is assumed to exist in S11 of 1x. This error will cause the de-embedded results to vary within a certain range. The upper bound and lower bound of the magnitude of the de-embedded results are given.
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