2,138 research outputs found
On spherical averages of radial basis functions
A radial basis function (RBF) has the general form
where the coefficients a 1,…,a n are real numbers, the points, or centres, b 1,…,b n lie in ℝ d , and φ:ℝ d →ℝ is a radially symmetric function. Such approximants are highly useful and enjoy rich theoretical properties; see, for instance (Buhmann, Radial Basis Functions: Theory and Implementations, [2003]; Fasshauer, Meshfree Approximation Methods with Matlab, [2007]; Light and Cheney, A Course in Approximation Theory, [2000]; or Wendland, Scattered Data Approximation, [2004]). The important special case of polyharmonic splines results when φ is the fundamental solution of the iterated Laplacian operator, and this class includes the Euclidean norm φ(x)=‖x‖ when d is an odd positive integer, the thin plate spline φ(x)=‖x‖2log ‖x‖ when d is an even positive integer, and univariate splines. Now B-splines generate a compactly supported basis for univariate spline spaces, but an analyticity argument implies that a nontrivial polyharmonic spline generated by (1.1) cannot be compactly supported when d>1. However, a pioneering paper of Jackson (Constr. Approx. 4:243–264, [1988]) established that the spherical average of a radial basis function generated by the Euclidean norm can be compactly supported when the centres and coefficients satisfy certain moment conditions; Jackson then used this compactly supported spherical average to construct approximate identities, with which he was then able to derive some of the earliest uniform convergence results for a class of radial basis functions. Our work extends this earlier analysis, but our technique is entirely novel, and applies to all polyharmonic splines. Furthermore, we observe that the technique provides yet another way to generate compactly supported, radially symmetric, positive definite functions. Specifically, we find that the spherical averaging operator commutes with the Fourier transform operator, and we are then able to identify Fourier transforms of compactly supported functions using the Paley–Wiener theorem. Furthermore, the use of Haar measure on compact Lie groups would not have occurred without frequent exposure to Iserles’s study of geometric integration
Thinplate Splines on the Sphere
In this paper we give explicit closed forms for the semi-reproducing kernels
associated with thinplate spline interpolation on the sphere. Polyharmonic or
thinplate splines for were introduced by Duchon and have become
a widely used tool in myriad applications. The analogues for are the thin plate splines for the sphere. The topic was first
discussed by Wahba in the early 1980's, for the case. Wahba
presented the associated semi-reproducing kernels as infinite series. These
semi-reproducing kernels play a central role in expressions for the solution of
the associated spline interpolation and smoothing problems. The main aims of
the current paper are to give a recurrence for the semi-reproducing kernels,
and also to use the recurrence to obtain explicit closed form expressions for
many of these kernels. The closed form expressions will in many cases be
significantly faster to evaluate than the series expansions. This will enhance
the practicality of using these thinplate splines for the sphere in
computations
Vector splines on the sphere with application to the estimation of vorticity and divergence from discrete, noisy data
Vector smoothing splines on the sphere are defined. Theoretical properties are briefly alluded to. The appropriate Hilbert space norms used in a specific meteorological application are described and justified via a duality theorem. Numerical procedures for computing the splines as well as the cross validation estimate of two smoothing parameters are given. A Monte Carlo study is described which suggests the accuracy with which upper air vorticity and divergence can be estimated using measured wind vectors from the North American radiosonde network
The Surface Laplacian Technique in EEG: Theory and Methods
This paper reviews the method of surface Laplacian differentiation to study
EEG. We focus on topics that are helpful for a clear understanding of the
underlying concepts and its efficient implementation, which is especially
important for EEG researchers unfamiliar with the technique. The popular
methods of finite difference and splines are reviewed in detail. The former has
the advantage of simplicity and low computational cost, but its estimates are
prone to a variety of errors due to discretization. The latter eliminates all
issues related to discretization and incorporates a regularization mechanism to
reduce spatial noise, but at the cost of increasing mathematical and
computational complexity. These and several others issues deserving further
development are highlighted, some of which we address to the extent possible.
Here we develop a set of discrete approximations for Laplacian estimates at
peripheral electrodes and a possible solution to the problem of multiple-frame
regularization. We also provide the mathematical details of finite difference
approximations that are missing in the literature, and discuss the problem of
computational performance, which is particularly important in the context of
EEG splines where data sets can be very large. Along this line, the matrix
representation of the surface Laplacian operator is carefully discussed and
some figures are given illustrating the advantages of this approach. In the
final remarks, we briefly sketch a possible way to incorporate finite-size
electrodes into Laplacian estimates that could guide further developments.Comment: 43 pages, 8 figure
Mathematical interpolation methods for spatial estimation of global horizontal irradiation in Castilla-León, Spain: a case study
Four spatial interpolation methods (Inverse Distance Weighted, Spline, Kriging and Natural Neighbor) and their different variations are employed to map Global Horizontal Irradiation (GHI) in Castilla-León, Spain. The work has been performed using the software ArcGis, widely used in geostatistical applications, showing the versatility of the system and its applicability to climate data. The measuring network consists of 71 ground meteorological stations that use seven complete years of half-hourly data sets, yielding annual daily averages of GHI. The interpolation results are tested against data from the four Spanish National Meteorological Agency (AEMET) stations available in the region using standard statistical indicators (RMSE, MBE, MAPE and MAE). An additional partial cross validation of the results, which excludes five stations from the measuring network, employs different criteria to verify the results of the interpolation methods applied. This work contributes to the classification of interpolation methods to obtain climatological data across large areas with a low number of irregularly distributed of measurement points and with a low topographic complexity. The Universal Kriging method with quadratic semi-variogram shows the best results taking into account the RMSE and MAE statistical indicatorsSpanish
Government (Grant ENE2014-54601-R) and Junta de Castilla-
León (BU034U16). One of the authors, David González Peña, thanks
to Junta de Castilla-León and European Social Fund (Orden
EDU/310/2015) for financial support
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