Levenberg–Marquardt method with general convex penalty for nonlinear inverse problems
Z Fu, B Han, Y Chen - Journal of Computational and Applied Mathematics, 2022 - Elsevier
Z Fu, B Han, Y Chen
Journal of Computational and Applied Mathematics, 2022•ElsevierAbstract We consider a Levenberg–Marquardt method for solving nonlinear inverse
problems in Hilbert spaces. The proposed method uses general convex penalty terms to
reconstruct nonsmooth solutions of inverse problems. Instead of an a priori choice, the
regularization parameter in each iteration is chosen by solving an equation which depends
on the residual. We utilize the discrepancy principle to terminate the iteration and give the
convergence results. In addition, numerical simulations are presented to test the …
problems in Hilbert spaces. The proposed method uses general convex penalty terms to
reconstruct nonsmooth solutions of inverse problems. Instead of an a priori choice, the
regularization parameter in each iteration is chosen by solving an equation which depends
on the residual. We utilize the discrepancy principle to terminate the iteration and give the
convergence results. In addition, numerical simulations are presented to test the …
Abstract
We consider a Levenberg–Marquardt method for solving nonlinear inverse problems in Hilbert spaces. The proposed method uses general convex penalty terms to reconstruct nonsmooth solutions of inverse problems. Instead of an a priori choice, the regularization parameter in each iteration is chosen by solving an equation which depends on the residual. We utilize the discrepancy principle to terminate the iteration and give the convergence results. In addition, numerical simulations are presented to test the performance of the method.
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