The complexity and heterogeneity of neuroimaging findings in individuals with autism spectrum disorder has suggested that many of the underlying alterations are subtle and involve many brain regions and networks. The ability to account for multivariate brain features and identify neuroimaging measures that can be used to characterize individual variation have thus become increasingly important ...

This report describes a simulation model of sonar tracking, developed to explore the effect of networking sonars on tracking performance. The tracker is an extended Kalman filter with data association by nearest-neighbour in Mahalanobis distance. Data fusion algorithms also use Mahalanobis distance. Simulation outputs have been verified against analytical results where possible.

I discuss diagnostic methods for discriminant analysis. The equivalence with linear regression is noted and regression diagnostics are considered. The leverage is a function of the linear discriminant function and the Mahalanobis distance of the observation from the group mean. The distribution of this distance is approximately chi-square with degrees of freedom equal to the number of variables...

Representing motions as linear sums of principal components has become a widely accepted animation technique. While powerful, the simplest version of this approach is not particularly well suited to modeling the specific style of an individual whose motion had not yet been recorded when building the database: It would take an expert to adjust the PCA weights to obtain a motion style that is ind...

In this paper we address the problem of measuring the degree of consensus/dissensus in a context where experts or agents express their opinions on alternatives or issues by means of cardinal evaluations. To this end we propose a new class of distance-based consensus model, the family of the Mahalanobis dissensus measures for profiles of cardinal values. We set forth some meaningful properties o...