Abstract
The Feature Selective Validation (FSV) method is currently the only technique included in Standards that is specifically directed at quantifying the comparison of computational electromagnetics with a reference as part of a programme of validation. Histogram representation of the Difference Measures in FSV is a key aspect of the way in which the comparison data is represented. The current six categories (or bins) were introduced for convenience and to allow direct comparison with visual assessment as part of the verification of FSV performance. While approaches based on continuous density functions are being developed to enable FSV to act as an intermediate step between the original data and statistical analysis, the use of histogram-based representation remains a useful and computationally simple approach. This paper investigates the optimization of the histograms used in FSV.
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