Down-sampled and Under-sampled Data sets in Feature Selective Validation (FSV)
Feature Selective Validation (FSV) is a heuristic method for quantifying the (dis)similarity of two data sets. The computational burden of obtaining the FSV values might be unnecessarily high if data sets with large numbers of points are used. While this may not be an important issue per se it is an important issue for future developments in FSV such as real-time processing or where multi-dimensional FSV is needed. Coupled with the issue of data set size, is the issue of data sets having ‘missing’ values. This may come about because of a practical difficulty or because of noise or other confounding factors making some data points unreliable. These issues relate to the question “what is the effect on FSV quantification of reducing or removing data points from a comparison – i.e. down- or under-sampling data?” This paper uses three strategies to achieve this from known data sets. This paper demonstrates, through a representative sample of 16 pairs of data sets, that FSV is robust to changes providing a minimum data set size of approximately 200 points is maintained. It is robust also for up to approximately 10% ‘missing’ data, providing this does not result in a continuous region of missed data.
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
Citation : G. Zhang et al. (2014) Downsampled and Undersampled Datasets in Feature Selective Validation (FSV). IEEE Transactions on Electromagnetic Compatibility, 56 (4), pp. 817-824
Research Group : Centre for Electronic and Communications Engineering
Research Institute : Institute of Engineering Sciences (IES)
Peer Reviewed : Yes
Showing items related by title, author, creator and subject.
Kim, Jong Man (Thesis or dissertation / Doctoral / PhD)
A flow sensitive security model is presented to analyse information flow in federated cloud systems. Each cloud and the entities of the cloud system are classified into different security levels which form a security ...
Performance optimization of polymeric collectors by means of dynamic simulation and sensitivity analysis Reiter, C.; Brandmayr, S.; Trinkl, Christoph; Zoerner, W.; Hanby, V. I. (Victor Ian), 1942- (Conference)The contribution analyses the performance compromise necessary to avoid high stagnation temperatures in polymeric solar collectors.