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Chebyshev wavelet-Picard technique for solving fractional nonlinear differential equations

  • Xiaoyong Xu EMAIL logo and Fengying Zhou
Published/Copyright: October 4, 2022

Abstract

In the present paper, an efficient method based on a new kind of Chebyshev wavelet together with Picard technique is developed for solving fractional nonlinear differential equations with initial and boundary conditions. The new orthonormal Chebyshev wavelet basis is constructed from a class of orthogonal polynomials called the fifth-kind Chebyshev polynomials. The convergence analysis and error estimation of the proposed Chebyshev wavelet expansion are studied. An exact formula for the Riemann-Liouville fractional integral of the Chebyshev wavelet is derived. Picard iteration is used to convert the fractional nonlinear differential equations into a fractional recurrence relation and then the proposed Chebyshev wavelet collocation method is applied on the converted problem. Several test problems are given to illustrate the performance and effectiveness of the proposed method and compared with the existing work in the literature.


Corresponding author: Xiaoyong Xu, School of Science, East China University of Technology, Nanchang, Jiangxi 330013, China, E-mail:

Funding source: Doctoral Scientific Research Foundation of East China University of Technology

Award Identifier / Grant number: DHBK2019213

Award Identifier / Grant number: 2020BABL201006

Award Identifier / Grant number: 41962019

Acknowledgement

The authors would like to thank the referees for their very helpful and detailed comments, which have significantly improved the presentation of this paper.

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: This work was supported by the National Natural Science Foundation of China (Grant No.41962019), the Natural Science Foundation of Jiangxi Province of China (Grant No.2020BABL201006) and the Doctoral Scientific Research Foundation of East China University of Technology (Grant No. DHBK2019213).

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

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Received: 2021-11-02
Accepted: 2022-09-18
Published Online: 2022-10-04

© 2022 Walter de Gruyter GmbH, Berlin/Boston

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