5,445 research outputs found
RBF multiscale collocation for second order elliptic boundary value problems
In this paper, we discuss multiscale radial basis function collocation methods for solving elliptic partial differential equations on bounded domains. The approximate solution is constructed in a multi-level fashion, each level using compactly supported radial basis functions of smaller scale on an increasingly fine mesh. On each level, standard symmetric collocation is employed. A convergence theory is given, which builds on recent theoretical advances for multiscale approximation using compactly supported radial basis functions. We are able to show that the convergence is linear in the number of levels. We also discuss the condition numbers of the arising systems and the effect of simple, diagonal preconditioners, now proving rigorously previous numerical observations
Zooming from Global to Local: A Multiscale RBF Approach
Because physical phenomena on Earth's surface occur on many different length
scales, it makes sense when seeking an efficient approximation to start with a
crude global approximation, and then make a sequence of corrections on finer
and finer scales. It also makes sense eventually to seek fine scale features
locally, rather than globally. In the present work, we start with a global
multiscale radial basis function (RBF) approximation, based on a sequence of
point sets with decreasing mesh norm, and a sequence of (spherical) radial
basis functions with proportionally decreasing scale centered at the points. We
then prove that we can "zoom in" on a region of particular interest, by
carrying out further stages of multiscale refinement on a local region. The
proof combines multiscale techniques for the sphere from Le Gia, Sloan and
Wendland, SIAM J. Numer. Anal. 48 (2010) and Applied Comp. Harm. Anal. 32
(2012), with those for a bounded region in from Wendland, Numer.
Math. 116 (2012). The zooming in process can be continued indefinitely, since
the condition numbers of matrices at the different scales remain bounded. A
numerical example illustrates the process
Multi-Level quasi-Newton methods for the partitioned simulation of fluid-structure interaction
In previous work of the authors, Fourier stability analyses have been performed of Gauss-Seidel iterations between the flow solver and the structural solver in a partitioned fluid-structure interaction simulation. These analyses of the flow in an elastic tube demonstrated that only a number of Fourier modes in the error on the interface displacement are unstable. Moreover, the modes with a low wave number are most unstable and these modes can be resolved on a coarser grid. Therefore, a new class of quasi-Newton methods with more than one grid level is introduced. Numerical experiments show a significant reduction in run time
On explicit results at the intersection of the Z_2 and Z_4 orbifold subvarieties in K3 moduli space
We examine the recently found point of intersection between the Z_2 and Z_4
orbifold subvarieties in the K3 moduli space more closely. First we give an
explicit identification of the coordinates of the respective Z_2 and Z_4
orbifold theories at this point. Secondly we construct the explicit
identification of conformal field theories at this point and show the
orthogonality of the two subvarieties.Comment: Latex, 23 page
Oscillatory combustion in rockets Third semiannual report, Jun. 1 - Nov. 30, 1965
Rocket engine oscillatory combustion studie
Multiscale approximation for functions in arbitrary Sobolev spaces by scaled radial basis functions on the unit sphere
AbstractIn this paper, we prove convergence results for multiscale approximation using compactly supported radial basis functions restricted to the unit sphere, for target functions outside the reproducing kernel Hilbert space of the employed kernel
Local RBF approximation for scattered data fitting with bivariate splines
In this paper we continue our earlier research [4] aimed at developing effcient methods of local approximation suitable for the first stage of a spline based two-stage scattered data fitting algorithm. As an improvement to the pure polynomial local approximation method used in [5], a hybrid polynomial/radial basis scheme was considered in [4], where the local knot locations for the RBF terms were selected using a greedy knot insertion algorithm. In this paper standard radial local approximations based on interpolation or least squares are considered and a faster procedure is used for knot selection, signicantly reducing the computational cost of the method. Error analysis of the method and numerical results illustrating its performance are given
TVL<sub>1</sub> Planarity Regularization for 3D Shape Approximation
The modern emergence of automation in many industries has given impetus to extensive research into mobile robotics. Novel perception technologies now enable cars to drive autonomously, tractors to till a field automatically and underwater robots to construct pipelines. An essential requirement to facilitate both perception and autonomous navigation is the analysis of the 3D environment using sensors like laser scanners or stereo cameras. 3D sensors generate a very large number of 3D data points when sampling object shapes within an environment, but crucially do not provide any intrinsic information about the environment which the robots operate within.
This work focuses on the fundamental task of 3D shape reconstruction and modelling from 3D point clouds. The novelty lies in the representation of surfaces by algebraic functions having limited support, which enables the extraction of smooth consistent implicit shapes from noisy samples with a heterogeneous density. The minimization of total variation of second differential degree makes it possible to enforce planar surfaces which often occur in man-made environments. Applying the new technique means that less accurate, low-cost 3D sensors can be employed without sacrificing the 3D shape reconstruction accuracy
Numerical Ricci-flat metrics on K3
We develop numerical algorithms for solving the Einstein equation on
Calabi-Yau manifolds at arbitrary values of their complex structure and Kahler
parameters. We show that Kahler geometry can be exploited for significant gains
in computational efficiency. As a proof of principle, we apply our methods to a
one-parameter family of K3 surfaces constructed as blow-ups of the T^4/Z_2
orbifold with many discrete symmetries. High-resolution metrics may be obtained
on a time scale of days using a desktop computer. We compute various geometric
and spectral quantities from our numerical metrics. Using similar resources we
expect our methods to practically extend to Calabi-Yau three-folds with a high
degree of discrete symmetry, although we expect the general three-fold to
remain a challenge due to memory requirements.Comment: 38 pages, 10 figures; program code and animations of figures
downloadable from http://schwinger.harvard.edu/~wiseman/K3/ ; v2 minor
corrections, references adde
A Statistical Model for Simultaneous Template Estimation, Bias Correction, and Registration of 3D Brain Images
Template estimation plays a crucial role in computational anatomy since it
provides reference frames for performing statistical analysis of the underlying
anatomical population variability. While building models for template
estimation, variability in sites and image acquisition protocols need to be
accounted for. To account for such variability, we propose a generative
template estimation model that makes simultaneous inference of both bias fields
in individual images, deformations for image registration, and variance
hyperparameters. In contrast, existing maximum a posterori based methods need
to rely on either bias-invariant similarity measures or robust image
normalization. Results on synthetic and real brain MRI images demonstrate the
capability of the model to capture heterogeneity in intensities and provide a
reliable template estimation from registration
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