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Farshid Mirzaee

Farshid Mirzaee

Academic rank: Professor
ORCID: 0000-0002-1429-2548
Education: PhD.
ScopusId: 6508385954
HIndex: 34/00
Faculty: Mathematical Sciences and Statistics
Address: Faculty of Mathematical Sciences and Statistics, Department of Applied Mathematics, Malayer University, 4 Km Malayer-Arak Road, P. O. Box 65719-95863, Malayer, Iran.
Phone: +98 - 81 - 32457459

Research

Title
Haar wavelet method for series expansion of fractional Wiener integrals
Type
JournalPaper
Keywords
Haar wavelet functions, Fractional wiener integrals, Brownian motion
Year
2019
Journal پژوهش هاي رياضي
DOI
Researchers Farshid Mirzaee

Abstract

The stochastic calculus plays an important role in the study of stochastic integral equations and stochastic differential equations. The fractional Brownian motion has many applications in different branches of sciences such as economics, physics and biology. In many situations, the exact solution of these equations are not available or finding their exact solution is a very difficult process. Thus, finding an accurate and efficient numerical method for solving stochastic differential equations, and stochastic integral equations is important. Researchers have applied various numerical methods such as Dirichlet forms, Euler approximation, Skorohod integral, etc. In this paper, we used Haar wavelet functions for solving fractional Wiener integrals. Moreover, the error analysis of the proposed method is investigated. Material and methods: In this scheme, first we present the properties of the Haar wavelet functions then an efficient method based on these functions is proposed to estimate the solution of fractional Wiener integral with Hurst parameter H (1/2, 1). Results and discussion: We solve two numerical examples by using present method to demonstrate the efficiency and simplicity of the present method. For different values of, mean of error and standard deviation of error are shown in the tables. The obtained results confirm that proposed method enables us to find reasonable approximate solutions. Conclusion: The Haar wavelet is the simplest possible wavelet, so proposed method is easy to implement and it is a powerful mathematical tool to obtain the numerical solution of various kind of problems.