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In this paper, a computational method is developed to find an approximate solution of the stochastic Volterra-Fredholm integral equation using the Walsh function approximation and its operational matrix. Moreover, convergence and error analysis of the method is carried out to strengthen the validity of the method. Furthermore, the method is numerically compared to the block pulse function method and the Haar wavelet method for some non-trivial examples.

Details

1009240
Subject
Error analysis;
Mathematical analysis;
Walsh function;
Wavelet analysis;
Integral equations;
Fredholm equations;
Approximation
Identifier / keyword
Numerical Analysis; Probability
URL
http://arxiv.org/abs/2305.16678
Title
Numerical Approximation of Stochastic Volterra-Fredholm Integral Equation using Walsh Function
Author
Prit Pritam Paikaray; Beuria, Sanghamitra; Parida, Nigam Chandra
Publication title
arXiv.org; Ithaca
Publication year
2023
Publication date
May 26, 2023
Section
Computer Science; Mathematics
Publisher
Cornell University Library, arXiv.org
Source
arXiv.org
Place of publication
Ithaca
Country of publication
United States
University/institution
Cornell University Library arXiv.org
Publication subject
Biology, Statistics, Physics, Mathematics, Engineering--Electrical Engineering, Computers--Computer Engineering, Business And Economics--Banking And Finance
e-ISSN
2331-8422
Source type
Working Paper
Language of publication
English
Document type
Working Paper
Publication history
 
 
Online publication date
2023-05-29
Milestone dates
2023-05-26 (Submission v1)
Publication history
 
 
   First posting date
29 May 2023
ProQuest document ID
2820199151
Document URL
https://www.proquest.com/working-papers/numerical-approximation-stochastic-volterra/docview/2820199151/se-2?accountid=208611
Full text outside of ProQuest
http://arxiv.org/abs/2305.16678
Copyright
© 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2023-05-30
Database
ProQuest One Academic