Results 31 to 40 of about 73 (67)
Natural alternatives for one dimensional median filtering
, 2004 For practical purposes median smoothers have often been considered the basic components for the construction of simple non-linear smoothers for removing impulsive noise before any subsequent linear signal extraction from a sequence.
Rohwer, CH, Wild, M
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Convex-Concave fitting to successively updated data and its application to covid-19 analysis. [PDF]
J Comb Optim, 2022 Davos DE, Demetriou IC.
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Splines on Riemannian Manifolds and a Proof of a Conjecture by Wahba
, 1999 This paper extends spline methods to compact Riemannian manifolds in an rkhs setting. The approach is to use the mathematical framework of rkhs, along with integrating spectral geometry associated with compact Riemannian manifolds.
Peter T. Kim
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Constrained Smoothing Splines Revisited
, 1997 In some regression settings one would like to combine the flexibility of nonparametric smoothing with some prior knowledge about the regression curve. Such prior knowledge may come from a physical or economic theory, leading to shape constraints such as ...
Berwin A. Turlach
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Variation reduction and LULU-Smoothing
, 2004 In the space of absolutely summable sequences the total variation of a sequence becomes a natural norm, and is a measure of smoothness. This norm is preserved by the so-called LULU-smoothers, in that the variation of the image plus the variation of the ...
Rohwer, CH
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On the Approximation Power of Bivariate Splines
, 1996 . We show how to construct stable quasi-interpolation schemes in the bivariate spline spaces S r d (4) with d 3r+2 which achieve optimal approximation order.
Larry L. Schumaker, Ming-jun Lai
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The hat matrix for smoothing splines
The matrix which transforms the data vector to the vector of fitted values for smoothing splines is termed the hat matrix. This matrix is shown to have many of the same properties, and is seen to play the same role in the variances and covariances of the
Eubank, R. L.
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Construction Techniques for Highly Accurate Quasi-Interpolation Operators
, 1996 : Under mild additional assumptions this paper constructs quasi-interpolants in the form f h (x) = +1 X j=\Gamma1 f(hj)' h i x h \Gamma j j ; x 2 IR; h ?
Zongmin Wu, Robert Schaback, R. Schaback
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Scattered Data Interpolation Using C² Supersplines Of Degree Six
, 1995 . We show how C 2 supersplines of degree 6 can be used to interpolate Hermite data at the vertices of a quadrangulation. We also present error bounds which show that our method has full approximation order 7, and compare its efficiency with other C 2
Larry Schumaker, Ming-jun Lai
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, 2001 We present a new approach to the classi cation problem arising in data mining. It is based on the regularization network approach but, in contrast to the other methods which employ ansatz functions associated to data points, we use a grid in the usually ...
M. Griebel, M. Thess, J. Garcke
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