788 research outputs found
Recommended from our members
Riemannian Geometries on Spaces of Plane Curves
We study some Riemannian metrics on the space of regular smooth curves in the plane, viewed as the orbit space of maps from the circle to the plane modulo the group of diffeomorphisms of the circle, acting as reparameterizations. In particular we investigate the L^2 inner product with respect to 1 plus curvature squared times arclength as the measure along a curve, applied to normal vector field to the curve. The curvature squared term acts as a sort of geometric Tikhonov regularization because, without it, the geodesic distance between any 2 distinct curves is 0, while in our case the distance is always positive. We give some lower bounds for the distance function, derive the geodesic equation and the sectional curvature, solve the geodesic equation with simple endpoints numerically, and pose some open questions. The space has an interesting split personality: among large smooth curves, all its sectional curvatures are positive or 0, while for curves with high curvature or perturbations of high frequency, the curvatures are negative.Mathematic
Uniform Penalty inversion of two-dimensional NMR Relaxation data
The inversion of two-dimensional NMR data is an ill-posed problem related to
the numerical computation of the inverse Laplace transform. In this paper we
present the 2DUPEN algorithm that extends the Uniform Penalty (UPEN) algorithm
[Borgia, Brown, Fantazzini, {\em Journal of Magnetic Resonance}, 1998] to
two-dimensional data. The UPEN algorithm, defined for the inversion of
one-dimensional NMR relaxation data, uses Tikhonov-like regularization and
optionally non-negativity constraints in order to implement locally adapted
regularization. In this paper, we analyze the regularization properties of this
approach. Moreover, we extend the one-dimensional UPEN algorithm to the
two-dimensional case and present an efficient implementation based on the
Newton Projection method. Without any a-priori information on the noise norm,
2DUPEN automatically computes the locally adapted regularization parameters and
the distribution of the unknown NMR parameters by using variable smoothing.
Results of numerical experiments on simulated and real data are presented in
order to illustrate the potential of the proposed method in reconstructing
peaks and flat regions with the same accuracy
- …