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Published/Copyright:
February 1, 2022
Published Online: 2022-02-01
Published in Print: 2022-02-01
© 2022 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
- Frontmatter
- Research biography of a distinguished expert in the field of inverse problems: Professor Michael Victor Klibanov
- Unique continuation property of solutions to general second order elliptic systems
- Calculation of the gradient of Tikhonov’s functional in solving coefficient inverse problems for linear partial differential equations
- Finite-dimensional boundary uniform stabilization of the Boussinesq system in Besov spaces by critical use of Carleman estimate-based inverse theory
- Alternating direction based method for optimal control problem constrained by Stokes equation
- Direct and inverse scalar scattering problems for the Helmholtz equation in ℝ m
- Mathematical modelling of plasmonic strain sensors
- Finite-dimensional iteratively regularized processes with an a posteriori stopping for solving irregular nonlinear operator equations
- Stability and the inverse gravimetry problem with minimal data
Articles in the same Issue
- Frontmatter
- Research biography of a distinguished expert in the field of inverse problems: Professor Michael Victor Klibanov
- Unique continuation property of solutions to general second order elliptic systems
- Calculation of the gradient of Tikhonov’s functional in solving coefficient inverse problems for linear partial differential equations
- Finite-dimensional boundary uniform stabilization of the Boussinesq system in Besov spaces by critical use of Carleman estimate-based inverse theory
- Alternating direction based method for optimal control problem constrained by Stokes equation
- Direct and inverse scalar scattering problems for the Helmholtz equation in ℝ m
- Mathematical modelling of plasmonic strain sensors
- Finite-dimensional iteratively regularized processes with an a posteriori stopping for solving irregular nonlinear operator equations
- Stability and the inverse gravimetry problem with minimal data