scholarly journals The Method Based on Series Solution for Identifying an Unknown Source Coefficient on the Temperature Field in the Quasiperiodic Media

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Bingxian Wang ◽  
Chuanzhi Bai ◽  
M. Xu ◽  
L. P. Zhang
Keyword(s):  
Inverse Problem ◽  
Series Solution ◽  
Iteration Process ◽  
One Dimensional ◽  
Exact Data ◽  
Unknown Source ◽  
Convergence Results ◽  
Quasiperiodic Media ◽  
Iteration Processes ◽  
Heat Field

In this paper, we consider the reconstruction of heat field in one-dimensional quasiperiodic media with an unknown source from the interior measurement. The innovation of this paper is solving the inverse problem by means of two different homotopy iteration processes. The first kind of homotopy iteration process is not convergent. For the second kind of homotopy iteration process, a convergent result is proved. Based on the uniqueness of this inverse problem and convergence results of the second kind of homotopy iteration process with exact data, the results of two numerical examples show that the proposed method is efficient, and the error of the inversion solution r t is given.

scholarly journals A new iteration scheme for approximating fixed points of nonexpansive mappings

Filomat ◽  
2016 ◽  
Vol 30 (10) ◽  
pp. 2711-2720 ◽  
Author(s):  
Balwant Thakur ◽  
Dipti Thakur ◽  
Mihai Postolache
Keyword(s):  
Banach Space ◽  
Fixed Point ◽  
Fixed Points ◽  
Nonexpansive Mappings ◽  
Iteration Process ◽  
Iteration Scheme ◽  
Numerical Example ◽  
Convergence Results ◽  
Iteration Processes

In this paper, we introduce a new three-step iteration scheme and establish convergence results for approximation of fixed points of nonexpansive mappings in the framework of Banach space. Further, we show that the new iteration process is faster than a number of existing iteration processes. To support the claim, we consider a numerical example and approximated the fixed point numerically by computer using MATLAB.

scholarly journals On Picard–Krasnoselskii Hybrid Iteration Process in Banach Spaces

2020 ◽  
Vol 2020 ◽  
pp. 1-5 ◽  
Author(s):  
Thabet Abdeljawad ◽  
Kifayat Ullah ◽  
Junaid Ahmad
Keyword(s):  
Banach Space ◽  
Weak Convergence ◽  
Banach Spaces ◽  
Nonexpansive Mappings ◽  
Iteration Process ◽  
Numerical Example ◽  
Strong And Weak Convergence ◽  
Convergence Results ◽  
Krasnoselskii Iteration ◽  
Iteration Processes

In this research, we prove strong and weak convergence results for a class of mappings which is much more general than that of Suzuki nonexpansive mappings on Banach space through the Picard–Krasnoselskii hybrid iteration process. Using a numerical example, we prove that the Picard–Krasnoselskii hybrid iteration process converges faster than both of the Picard and Krasnoselskii iteration processes. Our results are the extension and improvement of many well-known results of the literature.

scholarly journals Approximating common fixed points by a new faster iteration process

Filomat ◽  
2020 ◽  
Vol 34 (6) ◽  
pp. 2047-2060 ◽  
Author(s):  
Chanchal Garodia ◽  
Izhar Uddin ◽  
Safeer Khan
Keyword(s):  
Weak Convergence ◽  
Fixed Points ◽  
Nonexpansive Mappings ◽  
Iteration Process ◽  
Common Fixed Points ◽  
Numerical Example ◽  
Strong And Weak Convergence ◽  
Convergence Results ◽  
Iteration Processes

In this paper, we propose a three-step iteration process and show that this process converges faster than a number of existing iteration processes. We give a numerical example followed by graphs to validate our claim. We prove strong and weak convergence results for approximating common fixed points for two nonexpansive mappings. Again we reconfirm our results by examples and tables. Further, we provide some applications of the our iteration process.

scholarly journals A decomposition method for a semilinear boundary value problem with a quadratic nonlinearity

2005 ◽  
Vol 2005 (6) ◽  
pp. 855-861 ◽  
Author(s):  
Michael S. Gordon
Keyword(s):  
Boundary Value Problem ◽  
Decomposition Method ◽  
Series Solution ◽  
Boundary Value ◽  
Quadratic Nonlinearity ◽  
One Dimensional ◽  
Semilinear Heat Equation ◽  
Convergence Results ◽  
Dimensional Boundary ◽  
Local And Global Convergence

The author adapts the decomposition method of Adomian to find a series solution of a one-dimensional boundary value problem for a semilinear heat equation with a quadratic nonlinearity. Local and global convergence results are obtained.

scholarly journals Inverse problem for fractional diffusion equation

2011 ◽  
Vol 14 (1) ◽  
Author(s):  
Vu Tuan
Keyword(s):  
Inverse Problem ◽  
Diffusion Coefficient ◽  
Lower Bound ◽  
Diffusion Equation ◽  
Spectral Data ◽  
A Priori ◽  
Fractional Diffusion ◽  
Fractional Diffusion Equation ◽  
One Dimensional ◽  
Initial Distributions

AbstractWe prove that by taking suitable initial distributions only finitely many measurements on the boundary are required to recover uniquely the diffusion coefficient of a one dimensional fractional diffusion equation. If a lower bound on the diffusion coefficient is known a priori then even only two measurements are sufficient. The technique is based on possibility of extracting the full boundary spectral data from special lateral measurements.

scholarly journals Numerical method of identification of an unknown source term in a heat equation

2002 ◽  
Vol 8 (2) ◽  
pp. 161-168 ◽  
Author(s):  
Afet Golayoğlu Fatullayev
Keyword(s):  
Inverse Problem ◽  
Heat Equation ◽  
Numerical Method ◽  
Minimization Problem ◽  
Unknown Function ◽  
Source Term ◽  
Numerical Procedure ◽  
Numerical Examples ◽  
Unknown Source

A numerical procedure for an inverse problem of identification of an unknown source in a heat equation is presented. Approach of proposed method is to approximate unknown function by polygons linear pieces which are determined consecutively from the solution of minimization problem based on the overspecified data. Numerical examples are presented.

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