Inverse source problem in a space fractional diffusion equation from the final overdetermination

We consider the problem of determining the unknown source term f = f ( x,t ) in a space fractional diffusion equation from the measured data at the final time u ( x,T ) = ψ ( x ). In this way, a methodology involving minimization of the cost functional J ( f ) = ∫ l 0 ( u ( x, t ; f ) t=T − ψ ( x ))...

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Published inApplications of mathematics (Prague) Vol. 64; no. 4; pp. 469 - 484
Main Authors Salehi Shayegan, Amir Hossein, Tajvar, Reza Bayat, Ghanbari, Alireza, Safaie, Ali
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2019
Springer Nature B.V
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Abstract We consider the problem of determining the unknown source term f = f ( x,t ) in a space fractional diffusion equation from the measured data at the final time u ( x,T ) = ψ ( x ). In this way, a methodology involving minimization of the cost functional J ( f ) = ∫ l 0 ( u ( x, t ; f ) t=T − ψ ( x )) 2 d x is applied and shown that this cost functional is Fréchet differentiable and its derivative can be formulated via the solution of an adjoint problem. In addition, Lipschitz continuity of the gradient is proved. These results help us to prove the monotonicity and convergence of the sequence { J′ ( f ( n ) )}, where f ( n ) is the n th iteration of a gradient like method. At the end, the convexity of the Fréchet derivative is given.
AbstractList We consider the problem of determining the unknown source term f = f ( x,t ) in a space fractional diffusion equation from the measured data at the final time u ( x,T ) = ψ ( x ). In this way, a methodology involving minimization of the cost functional J ( f ) = ∫ l 0 ( u ( x, t ; f ) t=T − ψ ( x )) 2 d x is applied and shown that this cost functional is Fréchet differentiable and its derivative can be formulated via the solution of an adjoint problem. In addition, Lipschitz continuity of the gradient is proved. These results help us to prove the monotonicity and convergence of the sequence { J′ ( f ( n ) )}, where f ( n ) is the n th iteration of a gradient like method. At the end, the convexity of the Fréchet derivative is given.
We consider the problem of determining the unknown source term f = f(x,t) in a space fractional diffusion equation from the measured data at the final time u(x,T) = ψ(x). In this way, a methodology involving minimization of the cost functional J(f) = ∫l0(u(x, t; f)t=T − ψ(x))2 dx is applied and shown that this cost functional is Fréchet differentiable and its derivative can be formulated via the solution of an adjoint problem. In addition, Lipschitz continuity of the gradient is proved. These results help us to prove the monotonicity and convergence of the sequence {J′(f(n))}, where f(n) is the nth iteration of a gradient like method. At the end, the convexity of the Fréchet derivative is given.
Author Ghanbari, Alireza
Salehi Shayegan, Amir Hossein
Safaie, Ali
Tajvar, Reza Bayat
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Keywords space fractional diffusion equation
adjoint problem
inverse source problem
weak solution theory
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Snippet We consider the problem of determining the unknown source term f = f ( x,t ) in a space fractional diffusion equation from the measured data at the final time...
We consider the problem of determining the unknown source term f = f(x,t) in a space fractional diffusion equation from the measured data at the final time...
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SubjectTerms Analysis
Applications of Mathematics
Classical and Continuum Physics
Convexity
Diffusion
Mathematical analysis
Mathematical and Computational Engineering
Mathematical and Computational Physics
Mathematics
Mathematics and Statistics
Optimization
Theoretical
Title Inverse source problem in a space fractional diffusion equation from the final overdetermination
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