EconPapers    
Economics at your fingertips  
 

An efficient approximation technique applied to a non-linear Lane–Emden pantograph delay differential model

Mohammad Izadi and H.M. Srivastava

Applied Mathematics and Computation, 2021, vol. 401, issue C

Abstract: The primary focus of our work is to propose a computationally effective approximation algorithm to find the numerical solution of the so-called a new design of second-order Lane–Emden pantograph delayed problem with singularity and non-linearity. Our approach based upon the novel Bessel matrix representation together with the collocation points which transforms the newly designed model problem into a non-linear fundamental matrix equation. To testify the validity and applicability of the proposed method, three test examples with non-linearity are given. The computational results are accurate as compared with the exact solutions as well as with those of numerical values reported in the literature.

Keywords: Bessel functions; Collocation method; Delay differential equation; Lane–Emden equation; Pantograph differential equation; Singular initial-value problems (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0096300321001715
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:401:y:2021:i:c:s0096300321001715

DOI: 10.1016/j.amc.2021.126123

Access Statistics for this article

Applied Mathematics and Computation is currently edited by Theodore Simos

More articles in Applied Mathematics and Computation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:apmaco:v:401:y:2021:i:c:s0096300321001715