Discrete Laplace transform for interval-valued functions and its applications to interval fractional difference equations

IF 3.2 1区 数学 Q2 COMPUTER SCIENCE, THEORY & METHODS
Xuelong Liu, Guoju Ye, Wei Liu
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引用次数: 0

Abstract

This work aims to present a discrete Laplace transform for handling interval fractional difference equations. We first deal with algebraic properties of the forward gH-difference operator for interval-valued functions. In particular, the forward gH-difference operator of the product of a real function and an interval-valued function is studied, which is then applied to establish summation by parts of interval-valued functions. Moreover, we present the new concept of discrete Laplace transform for interval-valued functions and study some relevant properties. The discrete Laplace transform formula on forward gH-difference operators is derived by applying summation by parts. Finally, the analytic solution of the interval Caputo fractional difference equations is established by means of the discrete Laplace transform. The results developed in this paper are illustrated through several numerical examples.
区间值函数的离散拉普拉斯变换及其在区间分数阶差分方程中的应用
本文的目的是提出一个离散拉普拉斯变换来处理区间分数阶差分方程。我们首先讨论了区间值函数的正演h -差分算子的代数性质。特别地,研究了实函数与区间值函数乘积的正演h -差分算子,并将其应用于区间值函数的分部求和。提出了区间值函数离散拉普拉斯变换的新概念,并研究了相关性质。应用分部求和法,导出了正演h差分算子的离散拉普拉斯变换公式。最后,利用离散拉普拉斯变换建立了区间Caputo分数阶差分方程的解析解。通过几个数值算例说明了本文的结论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Fuzzy Sets and Systems
Fuzzy Sets and Systems 数学-计算机:理论方法
CiteScore
6.50
自引率
17.90%
发文量
321
审稿时长
6.1 months
期刊介绍: Since its launching in 1978, the journal Fuzzy Sets and Systems has been devoted to the international advancement of the theory and application of fuzzy sets and systems. The theory of fuzzy sets now encompasses a well organized corpus of basic notions including (and not restricted to) aggregation operations, a generalized theory of relations, specific measures of information content, a calculus of fuzzy numbers. Fuzzy sets are also the cornerstone of a non-additive uncertainty theory, namely possibility theory, and of a versatile tool for both linguistic and numerical modeling: fuzzy rule-based systems. Numerous works now combine fuzzy concepts with other scientific disciplines as well as modern technologies. In mathematics fuzzy sets have triggered new research topics in connection with category theory, topology, algebra, analysis. Fuzzy sets are also part of a recent trend in the study of generalized measures and integrals, and are combined with statistical methods. Furthermore, fuzzy sets have strong logical underpinnings in the tradition of many-valued logics.
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