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Interval Estimation of Polynomial Splines of the Fifth Order. / Бурова, Ирина Герасимовна; Вартанова, Анна Артуровна.

2017 FOURTH INTERNATIONAL CONFERENCE ON MATHEMATICS AND COMPUTERS IN SCIENCES AND IN INDUSTRY (MCSI). Том 2018-January 2017. стр. 293-297.

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборнике материалов конференциинаучнаяРецензирование

Harvard

Бурова, ИГ & Вартанова, АА 2017, Interval Estimation of Polynomial Splines of the Fifth Order. в 2017 FOURTH INTERNATIONAL CONFERENCE ON MATHEMATICS AND COMPUTERS IN SCIENCES AND IN INDUSTRY (MCSI). Том. 2018-January, стр. 293-297, 2017 Fourth International Conference on Mathematics and Computers in Sciences and in Industry (MCSI), 24/08/17. https://doi.org/10.1109/MCSI.2017.54

APA

Бурова, И. Г., & Вартанова, А. А. (2017). Interval Estimation of Polynomial Splines of the Fifth Order. в 2017 FOURTH INTERNATIONAL CONFERENCE ON MATHEMATICS AND COMPUTERS IN SCIENCES AND IN INDUSTRY (MCSI) (Том 2018-January, стр. 293-297) https://doi.org/10.1109/MCSI.2017.54

Vancouver

Бурова ИГ, Вартанова АА. Interval Estimation of Polynomial Splines of the Fifth Order. в 2017 FOURTH INTERNATIONAL CONFERENCE ON MATHEMATICS AND COMPUTERS IN SCIENCES AND IN INDUSTRY (MCSI). Том 2018-January. 2017. стр. 293-297 https://doi.org/10.1109/MCSI.2017.54

Author

Бурова, Ирина Герасимовна ; Вартанова, Анна Артуровна. / Interval Estimation of Polynomial Splines of the Fifth Order. 2017 FOURTH INTERNATIONAL CONFERENCE ON MATHEMATICS AND COMPUTERS IN SCIENCES AND IN INDUSTRY (MCSI). Том 2018-January 2017. стр. 293-297

BibTeX

@inproceedings{f03dd0445d294b6d8a6a895e31d8a0ca,
title = "Interval Estimation of Polynomial Splines of the Fifth Order",
abstract = "In many cases, approximation by local interpolating splines is preferable to approximation by interpolating polynomials or interpolating by other types of splines. In the case of integro-differential splines we use the values of integrals over net intervals. The main features of these splines are the following: the approximation is constructed separately for each grid interval (or elementary rectangular), the approximation constructed as the sum of products of the basic splines and the values of function in nodes and/or the values of its derivatives and/or the values of integrals of this function over subintervals. Basic splines are determined by using a solving system of equations which are provided by the set of functions. In this paper we present the estimation of approximation and the algorithm for constructing an interval extension of approximation when values of function in nodes, values of its first derivative in nodes, and values of its integrals over net intervals are given. The algorithm of approximation is based on the method of approximating functions using integro-differential splines. For constructing this interval extension, we use techniques from interval analysis. Numerical examples are given.",
keywords = "Approximation, Integro-differential splines, Polynomial interval extension, Tensor production",
author = "Бурова, {Ирина Герасимовна} and Вартанова, {Анна Артуровна}",
year = "2017",
doi = "10.1109/MCSI.2017.54",
language = "English",
volume = "2018-January",
pages = "293--297",
booktitle = "2017 FOURTH INTERNATIONAL CONFERENCE ON MATHEMATICS AND COMPUTERS IN SCIENCES AND IN INDUSTRY (MCSI)",
note = "2017 Fourth International Conference on Mathematics and Computers in Sciences and in Industry (MCSI) ; Conference date: 24-08-2017 Through 27-08-2017",

}

RIS

TY - GEN

T1 - Interval Estimation of Polynomial Splines of the Fifth Order

AU - Бурова, Ирина Герасимовна

AU - Вартанова, Анна Артуровна

PY - 2017

Y1 - 2017

N2 - In many cases, approximation by local interpolating splines is preferable to approximation by interpolating polynomials or interpolating by other types of splines. In the case of integro-differential splines we use the values of integrals over net intervals. The main features of these splines are the following: the approximation is constructed separately for each grid interval (or elementary rectangular), the approximation constructed as the sum of products of the basic splines and the values of function in nodes and/or the values of its derivatives and/or the values of integrals of this function over subintervals. Basic splines are determined by using a solving system of equations which are provided by the set of functions. In this paper we present the estimation of approximation and the algorithm for constructing an interval extension of approximation when values of function in nodes, values of its first derivative in nodes, and values of its integrals over net intervals are given. The algorithm of approximation is based on the method of approximating functions using integro-differential splines. For constructing this interval extension, we use techniques from interval analysis. Numerical examples are given.

AB - In many cases, approximation by local interpolating splines is preferable to approximation by interpolating polynomials or interpolating by other types of splines. In the case of integro-differential splines we use the values of integrals over net intervals. The main features of these splines are the following: the approximation is constructed separately for each grid interval (or elementary rectangular), the approximation constructed as the sum of products of the basic splines and the values of function in nodes and/or the values of its derivatives and/or the values of integrals of this function over subintervals. Basic splines are determined by using a solving system of equations which are provided by the set of functions. In this paper we present the estimation of approximation and the algorithm for constructing an interval extension of approximation when values of function in nodes, values of its first derivative in nodes, and values of its integrals over net intervals are given. The algorithm of approximation is based on the method of approximating functions using integro-differential splines. For constructing this interval extension, we use techniques from interval analysis. Numerical examples are given.

KW - Approximation

KW - Integro-differential splines

KW - Polynomial interval extension

KW - Tensor production

UR - http://www.scopus.com/inward/record.url?scp=85050338170&partnerID=8YFLogxK

U2 - 10.1109/MCSI.2017.54

DO - 10.1109/MCSI.2017.54

M3 - Conference contribution

VL - 2018-January

SP - 293

EP - 297

BT - 2017 FOURTH INTERNATIONAL CONFERENCE ON MATHEMATICS AND COMPUTERS IN SCIENCES AND IN INDUSTRY (MCSI)

T2 - 2017 Fourth International Conference on Mathematics and Computers in Sciences and in Industry (MCSI)

Y2 - 24 August 2017 through 27 August 2017

ER -

ID: 32594657