Modifying the feature-selective validation method to validate noisy data sets

Objective validation and ranking of measurements and simulations may be done by methods such as feature selective validation (FSV). FSV is used to compare two EMC-measurement results. Owing to the noisy nature of these type of data, the FSV results are corrupted. The reasons are discussed and solutions are proposed to make FSV feasible in a broader area of applications. The final solution is a combination of denoising the data and changing the weight of the data to be in accordance with our visual interpretation.