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Introduction to feature selective validation (FSV)

Introduction to feature selective validation (FSV),10.1109/APS.2006.1710595,Vignesh Rajamani,C. F. Bunting,A. Orlandi,A. Duffy

Introduction to feature selective validation (FSV)   (Citations: 4)
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The feature selective validation (FSV) tool is a standalone application that implements the FSV method originally developed by Dr Anthony Martin. The feature selective validation (FSV) algorithm has been developed to compare any two sets of data and put them in an objective and comprehensible form. The FSV theory was conceived as a technique to quantify the comparison of data sets by mirroring the perceptions of engineers. The application of FSV to the validation of data is a key element in a current IEEE Standard under development as a means of describing quality of electromagnetic simulation results. FSV allows automated comparisons of large volumes of complex data whilst reliably categorising the results into a common set of quality bands. The motivation behind this research can be summed up as the need to control variations between visual assessment results, the reduction of cost (a skilled engineer is an expensive commodity), the desire to reduce ambiguities and the inability of humans to process and cache extremely large volumes of data
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