First-order and second-order adjoint methods for parameter identification problems with an application to the elasticity imaging inverse problem-Reference-Cited by-同舟云学术

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First-order and second-order adjoint methods for parameter identification problems with an application to the elasticity imaging inverse problem

Published:2017-02-10 Issue:12 Volume:25 Page:1768-1787
ISSN:1741-5977
Container-title:Inverse Problems in Science and Engineering
language:en
Short-container-title:Inverse Problems in Science and Engineering

Author:

Jadamba Baasansuren¹,Khan Akhtar A.¹,Oberai Assad A.²,Sama Miguel³

Affiliation:

1. Center for Applied and Computational Mathematics, School of Mathematical Sciences, Rochester Institute of Technology, Rochester, NY, USA.

2. Scientific Research Computation Center (SCOREC), Rensselaer Polytechnic Institute, Troy, NY, USA.

3. Departamento de Matemática Aplicada, Universidad Nacional de Educación a Distancia, Madrid, Spain.

Publisher

Informa UK Limited

Subject

Applied Mathematics,Computer Science Applications,General Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/17415977.2017.1289195

Reference40 articles.

1. Numerical Computation of Sensitivities and the Adjoint Approach

2. Time domain topological gradient and time reversal analogy: an inverse method for ultrasonic target detection

3. Adjoint parameter sensitivity analysis for the hydrodynamic lattice Boltzmann method with applications to design optimization

4. Adjoint method for a tumor growth PDE-constrained optimization problem

Cited by 12 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Existence results and optimization over the set of efficient solutions in vector-valued approximation theory;Journal of Nonlinear and Variational Analysis;2023

2. Levenberg-Marquardt method for identifying Young's modulus of the elasticity imaging inverse problem;Electronic Research Archive;2022

3. Nonlinear conjugate gradient method for identifying Young's modulus of the elasticity imaging inverse problem;Inverse Problems in Science and Engineering;2021-04-02

4. An iteratively regularized stochastic gradient method for estimating a random parameter in a stochastic PDE. A variational inequality approach;Journal of Nonlinear and Variational Analysis;2021

5. A Variational Inequality Based Stochastic Approximation for Inverse Problems in Stochastic Partial Differential Equations;Springer Optimization and Its Applications;2020-09-30

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