Our preconditioning strategy is based on a known spectrally equivalent pre- conditioner for the Laplacian, which enters the problem by way of the regularization.
Apr 2, 2024 · Section 2 introduces the problem setting of \(H^1\)-regularized parameter estimation, derives the operator equations to be solved in each Gauss– ...
Abstract. We consider the identification of spatially distributed parameters under \(H^1\) regularization. Solving the associated minimization problem by ...
Sep 6, 2022 · Abstract:We consider the identification of spatially distributed parameters under H^1 regularization. Solving the associated minimization ...
Apr 5, 2024 · We investigate Morozov's discrepancy principle for choosing the regularization parameter in Tikhonov regularization for solving nonlinear ill- ...
Article on Efficient Solution of Parameter Identification Problems with \(H^1\) Regularization, published in SIAM Journal on Scientific Computing 46 on ...
We consider parameter identification problems for parameters distributed in space under H1 regular- ization. Linearization using the Gauss-Newton method ...
Missing: H^ | Show results with:H^
In this paper we consider PDE-constrained optimization problems which incorporate an H 1 regularization control term. We focus on a time-dependent PDE, ...
Sep 6, 2022 · A new regularization method for a parameter identification problem in a non-linear partial differential equation ... We consider a parameter ...
We consider the identification of spatially distributed parameters under$H^1$ regularization. Solving the associated minimization problem byGauss-Newton ...