In this paper a pair of wavelets are constructed on the basis of Hermite cubic splines. These wavelets are in C1 and supported on [−1, 1]. Moreover, one wavelet is symmetric, and the other is antisymmetric. These spline wavelets are then adapted to the interval [0, 1]. The construction of boundary wavelets is remarkably simple. Furthermore, global stability of the wavelet basis is established. ...

A new algorithm for Computer Aided Geometric Design of least squares (LS) splines with variable knots, named GeDS, is presented. It is based on interpreting functional spline regression as a parametric B-spline curve, and on using the shape preserving property of its control polygon. The GeDS algorithm includes two major stages. For the first stage, an automatic adaptive, knot location algorith...

This research deals with the use of a number statistical methods, such as kernel method, watershed, histogram, and cubic spline, to improve contrast digital images. The results obtained according RSME NCC standards have proven that spline method is most accurate in compared other methods.

Classification is the last, and usually most time-consuming step in recognition. Most recently proposed classification algorithms have adopted machine learning (ML) as main approach, regardless of time consumption. This study proposes a statistical feature cubic spline interpolation (FC-CSI) algorithm to classify emotions speech using curve fitting technique. FC-CSI utilized emotion recognition...

This paper presented the G1 cubic trigonometric spline function with three shape parameters that generate a constrained curve interpolates 2D data. The purpose of this research is to ensure generated passes through all data point yet satisfied cases line constraints given. are: must lie above Li below and lastly, between two lines Li,1 Li,2. A simpler theorem implemented involving roles paramet...

This paper considers nonparametric regression to analyze longitudinal data. Some developments of nonparametric regression have been achieved for longitudinal or clustered categorical data. For exponential family distribution, Lin & Carroll [6] considered nonparametric regression for longitudinal data using GEE-Local Polynomial Kernel (LPK). They showed that in order to obtain an efficient estim...