Abstract: This paper reconstructs multivariate functions from scattered data by a new multiscale technique. The reconstruction uses support vector regression model by positive definite reproducing ...

Recent advances in estimation techniques have underscored the growing importance of shrinkage estimation and balanced loss functions in the analysis of multivariate normal distributions. These ...

1 Institute of Mathematics, University of Lübeck, Lübeck, Germany 2 Institute of Mathematics, National Academy of Sciences of Ukraine, Kyiv, Ukraine This paper ...

This Python-module computes generating functions for the number of some special multivariate polynomials over finite fields. The accompanying paper [GVZ13] also ...

1 Faculty of Sciences of Bizerte, Carthage University, Tunis, Tunisia. 2 Faculty of Economics and Management of Nabeul, Carthage University, Tunis, Tunisia. This paper deals with the global ...

In this paper, the interpolation of multivariate data by operators of the neural network type is proved. These operators can also be used to approximate continuous functions defined on a box-domain of ...

This is a preview. Log in through your library . Abstract ABSTRACT A unified turbulence and cloud parameterization based on multivariate probability density functions (PDFs) has been incorporated into ...

If int, random_state is the seed used by the random number generator; If RandomState instance, random_state is the random number generator; If None, the random number generator is the RandomState ...

1 Faculty of Sciences of Bizerte, Carthage University, Tunis, Tunisia 2 Faculty of Economics and Management of Nabeul, Carthage University, Tunis, Tunisia This paper deals with the global optimization ...

Abstract: The first nonlinear rules for wavelet based image denoising assume wavelet coefficients are independent. However it is well known that there are strong dependencies between coefficients such ...