Abstract Within a covariant perturbative field-theoretical approach, the wave-packet modified neutrino propagator is expressed as an asymptotic expansion in powers of dimensionless Lorentz- and rotation-invariant variables. The valid at high energies short but macroscopic space-time distances between vertices proper Feynman macrodiagram. In terms duality effective wave packet, times distances, ...

We present an algorithm that computes the exact Hausdorff distance between two arbitrary triangular meshes. Our method computes squared distances for each point on each triangle of one mesh to all relevant triangles of the other mesh yielding a continuous, piecewise convex quadratic polynomial over domains bounded by conics. The maximum of this polynomial is the one-sided Hausdorff distance fro...

We present two novel bounds for the classification error that, at the same time, can be used as practical training criteria. Unlike the bounds reported in the literature so far, these novel bounds are based on a strict distinction between the true but unknown distribution and the model distribution, which is used in the decision rule. The two bounds we derive are the squared distance and the Ku...

We report on block-coding techniques for partial-response II. PRELIMINARY channels with transfer function (1 F Dm), m = 1,2, . . We consider various constructions of block codes with prescribed min imum Euclidean Let u = (x1,... ,un) andv = (VI,..., un) be two n-tuples over distance. Upper and lower bounds to the size of a code with min imum @ = {-l,l}. Define the difference vector e = (el,...,...

Geodesic regression generalizes linear regression to general Riemannian manifolds. Applied to images, it allows for a compact approximation of an image time-series through an initial image and an initial momentum. Geodesic regression requires the definition of a squared residual (squared distance) between the regression geodesic and the measurement images. In principle, this squared distance sh...