An Extended Primal-Dual Algorithm Framework for Nonconvex Problems with Application to Nonlinear Imaging

We propose an extended primal-dual algorithm framework for solving a general nonconvex optimization model. This work is motivated by image reconstruction problems in a class of nonlinear imaging, where the forward operator can be formulated as a nonlinear convex function with respect to the reconstr...

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Vydané v:	arXiv.org
Hlavní autori:	Gao, Yu, Pan, Xiaochuan, Chen, Chong
Médium:	Paper
Jazyk:	English
Vydavateľské údaje:	Ithaca Cornell University Library, arXiv.org 15.09.2021
Predmet:	Algorithms Computed tomography Convergence Image reconstruction Iterative methods Mathematical analysis Optimization
ISSN:	2331-8422
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