Challenges in developing a multidimensional Feature Selective Validation implementation

Feature Selective Validation (FSV) was incorporated as core component of IEEE Std 1597.1. Recently, discussions have moved from `is quantitative comparison of data needed?´ to `how can this be applied to multidimensional data?´ The purpose of this paper is to present some of the latest thinking about the key challenges in developing a 1D model to unlimited dimensionality. In particular, the paper will present: (1) a revised mathematical framework for FSV, e.g. using tensor notation to simplify the mathematical representation. (2) A discussion on how the performance of n Dimensional FSV can be verified against human perception. (3) A review on the effects of data that oscillates between positive and negative data points, e.g. transients.