Academic literature on the topic 'Cubic Spline'

A new interpolation spline with two parameters, called EH interpolation spline, is presented in this paper, which is the extension of the standard cubic Hermite interpolation spline, and inherits the same properties of the standard cubic Hermite interpolation spline. Given the fixed interpolation conditions, the shape of the proposed splines can be adjusted by changing the values of the parameters. Also, the introduced spline could approximate to the interpolated function better than the standard cubic Hermite interpolation spline and the quartic Hermite interpolation splines with single parameter by a new algorithm.

<p class="Abstrak">Interpolasi splin kubik merupakan sebuah metode pencocokan kurva yang sangat populer karena mudah diterapkan dan menghasilkan kurva yang mulus. Pada artikel ini dibahas pengembangan metode interpolasi splin kubik untuk syarat batas terapit yang diambil dari rumus eksplisit beda hingga dengan ketelitian orde lebih tinggi. Pengembangan metode ini diterapkan pada masalah pelacakan trajektori objek (<em>object tracking</em>). Secara khusus, masalah ini diujikan untuk splin kubik terapit orde dua, dan hasil interpolasinya dibandingkan dengan hasil pada splin kubik alami dan splin kubik terapit orde satu. Dari simulasi data trajektori yang dibangkitkan dari kurva spiral Archimedean, diperoleh nilai galat total untuk splin kubik alami, terapit orde satu dan terapit orde dua masing-masing sebagai berikut: , dan . Berdasarkan hasil tersebut, disimpulkan bahwa interpolasi splin kubik terapit orde dua yang dikembangkan pada artikel ini dapat menghasilkan trajektori objek yang lebih akurat dibandingkan splin kubik alami dan splin kubik terapit orde satu.</p><p class="Abstrak"> </p><p class="Abstrak"><em><strong>Abstrract</strong></em></p><p class="Abstract"><em>Cubic spline interpolation is a very popular curve fitting method since it is easy to implement and produces a smooth curve. This article discusses the development of the cubic spline interpolation method for a clamped boundary condition taken from finite-difference explicit formulas with higher-order accuracy. The development of this method is applied to an object tracking problem. In particular, this problem is examined for second-order clamped cubic spline, and the interpolated results are compared with those for natural and first-order clamped cubic splines. From the simulation of trajectory data generated from the Archimedean spiral curve, the total error values for natural, first-order, and second-order clamped cubic splines are respectively , and . Based on these results, it is concluded that the second-order clamped cubic spline interpolation developed in this article can produce a more accurate object trajectory than the natural and first-order clamped cubic splines.</em></p><p class="Abstrak"><em><strong><br /></strong></em></p>

From the result in [1] it follows that there is a unique quadratic spline which bounds the same area as that of the function. The matching of the area for the cubic spline does not follow from the corresponding result proved in [2]. We obtain cubic splines which preserve the area of the function.

Cubic spline histopolation with arbitrary placement of histogram knots and spline knots between them is studied. Classical boundary conditions are used. Histopolating spline is represented with the help of second moments and particular integrals. The systems determining these parameters are investigated in different cases where diagonal dominance in matrices takes place or may be absent.

In this paper a new kind of splines, called cubic trigonometric polynomial B-spline (cubic TP B-spline) curves with a shape parameter, are constructed over the space spanned by As each piece of the curve is generated by three consecutive control points, they posses many properties of the quadratic B-spline curves. These trigonometric curves with a non-uniform knot vector are C1 and G2 continuous. They are C2 continuous when choosing special shape parameter for non-uniform knot vector. These curves are closer to the control polygon than the quadratic B-spline curves when choosing special shape parameters. With the increase of the shape parameter, the trigonometric spline curves approximate to the control polygon. The given curves posses many properties of the quadratic B-spline curves. The generation of tensor product surfaces by these new splines is straightforward.

The work offers the solution to problems of analysis and synthesis of infocommunication systems with the help of real and complex spline functions. The use of the spline approximation method for solving problems of recovery of random signals and self-similar traffic, management of network objects and network as a whole, and procedures of infocommunication objects and networks functioning is offered. To solve the problems of forecasting, in particular, forecasting the characteristics of network traffic and maintaining the QoS characteristics in its service and formation of requirements for network buffer devices, developed spline extrapolation based on different types of real spline functions, namely: linear, quadratic, quadratic B-splines, cubic, cubic B-splines, cubic Hermite splines. As a criterion for choosing the type of spline function, the prediction error is selected, the accuracy of which can be increased by using a particular kind of spline, depending on the object being predicted. The use of complex flat spline functions is considered to solve the class of user positioning problems in the radio access network. In general, the use of real and complex spline functions allows obtaining the results of improving the Quality of Service in the infocommunication network and ensuring the scalability of the obtained solutions.

This paper considers the problem of predicting self-similar traffic with a significant number of pulsations and the property of long-term dependence, using various spline functions. The research work focused on the process of modeling self-similar traffic handled in a mobile network. A splineextrapolation method based on various spline functions (linear, cubic and cubic B-splines) is proposed to predict selfsimilar traffic outside the period of time in which packet data transmission occurs. Extrapolation of traffic for short- and long-term forecasts is considered. Comparison of the results of the prediction of self-similar traffic using various spline functions has shown that the accuracy of the forecast can be improved through the use of cubic B-splines. The results allow to conclude that it is advisable to use spline extrapolation in predicting self-similar traffic, thereby recommending this method for use in practice in solving traffic prediction-related problems.