A series of numerical examples is reported and several algorithms compared for estimation of coefficients in differential equation models. Unconstrained, constrained and Tikhonov regularization methods are tested for their behavior with regard to both convergence (of approximation methods for the states and parameters) and stability (continuity of the estimates with respect to perturbations in the data or observed states)
An abstract approximation framework for the identification of nonlinear distributed parameter system...
An abstract approximation framework and convergence theory for the identification of first and secon...
This report deals with the problem of guaranteed estimation of the state of a distri-buted system on...
A theoretical framework is presented that can be used to treat approximation techniques for very gen...
ABSTRACT 9 We present a theoretical framework that can be used to treat approximation techniques for...
AbstractThe theory of identification of variable coefficients in parabolic distributed parameter sys...
Convergence and stability results for least squares inverse problems involving systems described by ...
A theoretical framework for proposed "weak Tau" type of approximation schemes is considere...
summary:We give a derivation of an a-posteriori strategy for choosing the regularization parameter i...
In this work we analyze the inverse problem of recovering the space-dependent potential coefficient ...
The need to blend observational data and mathematical models arises in many applications and leads n...
Esta Tesis abarca el estudio de métodos de regularización para problemas inversos mal condicionados ...
Inverse problems constrained by partial differential equations (PDEs) play a critical role in model ...
Projet IDENTThis paper is devoted to the introduction and analysis of regularization in state space ...
This paper documents the consequences of the identification failures in a class of linear ill-posed ...
An abstract approximation framework for the identification of nonlinear distributed parameter system...
An abstract approximation framework and convergence theory for the identification of first and secon...
This report deals with the problem of guaranteed estimation of the state of a distri-buted system on...
A theoretical framework is presented that can be used to treat approximation techniques for very gen...
ABSTRACT 9 We present a theoretical framework that can be used to treat approximation techniques for...
AbstractThe theory of identification of variable coefficients in parabolic distributed parameter sys...
Convergence and stability results for least squares inverse problems involving systems described by ...
A theoretical framework for proposed "weak Tau" type of approximation schemes is considere...
summary:We give a derivation of an a-posteriori strategy for choosing the regularization parameter i...
In this work we analyze the inverse problem of recovering the space-dependent potential coefficient ...
The need to blend observational data and mathematical models arises in many applications and leads n...
Esta Tesis abarca el estudio de métodos de regularización para problemas inversos mal condicionados ...
Inverse problems constrained by partial differential equations (PDEs) play a critical role in model ...
Projet IDENTThis paper is devoted to the introduction and analysis of regularization in state space ...
This paper documents the consequences of the identification failures in a class of linear ill-posed ...
An abstract approximation framework for the identification of nonlinear distributed parameter system...
An abstract approximation framework and convergence theory for the identification of first and secon...
This report deals with the problem of guaranteed estimation of the state of a distri-buted system on...