We consider ®rst the spline smoothing nonparametric estimation with variable smoothing parameter and arbitrary design density function and show that the corresponding equivalent kernel can be approximated by the Green function of a certain linear differential operator. Furthermore, we propose to use the standard (in applied mathematics and engineering) method for asymptotic solution of linear d...

This paper introduces the effective speckle reduction of synthetic aperture radar (SAR) images using inner product spaces in undecimated wavelet domain. There are two major areas in projection onto span algorithm where improvement can be made. First is the use of undecimated wavelet transformation instead of discrete wavelet transformation. And second area is the use of smoothing filter namely ...

We consider several conventional mesh smoothing approaches such as the Laplacian and bilaplacian smoothing methods, mean curvature flow (implicit implementation), and the Taubin j scheme and give a quantitative evaluation of them. To compare two close meshes having the same connectivity we consider vertex-based and normalbased L2 error metrics. We also give a visual comparison of the methods. W...

We give a convergence estimate for a Petrov-Galerkin Algebraic Multigrid method. In this method, the prolongations are defined using the concept of smoothed aggregation while the restrictions are simple aggregation operators. The analysis is carried out by showing that these methods can be interpreted as variational Ritz-Galerkin ones using modified transfer and smoothing operators. The estimat...

This paper introduces the effective speckle reduction of synthetic aperture radar (SAR) images using inner product spaces in undecimated wavelet domain. There are two major areas in projection onto span algorithm where improvement can be made. First is the use of undecimated wavelet transformation instead of discrete wavelet transformation. And second area is the use of smoothing filter namely ...

Robust face recognition under various illumination environments is very difficult and needs to be accomplished for successful commercialization. In this paper, we propose an improved illumination normalization method for face recognition. Illumination normalization algorithm based on anisotropic smoothing is well known to be effective among illumination normalization methods but deteriorates th...

An important element of both exploratory data analysis and many dimensionality reduction techniques is a scatterplot smoother. In both areas there is a strong need for fast and simple procedures. A major hurdle is choice of the amount of smoothing. In this paper we propose a fast and simple choice of the scatterplot smoothing parameter, based on blockwise least squares parabolic tting. Our meth...

Transaction cost function minimization is an important problem in finance. In this essay, we develop and apply a simulated annealing and smoothing method to this particular problem. We illustrate that this method is an improvement over using the trust-region method or simulated annealing algorithm alone. We will provide examples in different dimensions and using different parameter settings to ...

Interval-valued time series are interval-valued data that are collected in a chronological sequence through time. This paper adapts an approach to forecasting interval valued-time series based on Holt’s exponential smoothing method. In the adapted Holt’s method for interval-valued time series, the smoothing parameters are estimated by using techniques for non-linear optimization problems with b...

One popular method for nonparametric spectral density estimation is to perform kernel smoothing on the periodogram, and one important component of this method is the choice of the bandwidth (or span) for smoothing. This paper proposes a new bandwidth selection method that is based on a coupling of the so-called plug-in and the unbiased risk estimation ideas. This new method is easy to describe,...