付振武 - 哈尔滨工业大学

个人简介

付振武，男，1991年出生于山东济宁。哈尔滨工业大学数学学院副教授，硕士生导师。主要研究方向为非线性反问题迭代正则化算法及其在全波形反演中的应用。入选2022年哈尔滨工业大学首届”小米青年学者“。在《Inverse Problems》、《SIAM Journal on Imaging Sciences》、《IMA Journal of Numerical Analysis》等杂志发表SCI论文10余篇，主持国家自然基金青年基金1项，中国博士后面上项目1项，参与国家自然科学基金面上项目3项。教育经历 2010.09-2014.06 数学与应用数学山东科技大学学士学位（指导教师：崔玉军教授） 2014.09-2016.07 应用数学哈尔滨工业大学硕士学位（指导教师：陈勇教授） 2016.09-2020.10 数学哈尔滨工业大学博士学位（指导教师：韩波教授、陈勇教授） 2017.12-2018.12 数学科学学院澳大利亚国立大学访问学者（合作导师：金其年教授）工作经历 2020.12--至今博士后哈尔滨工业大学合作导师：田浩教授 2021.12--2022.12 助理教授哈尔滨工业大学数学学院 2023.01--至今副教授哈尔滨工业大学数学学院

研究领域

反问题及应用

近期论文

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Heuristic rule for inexact Newton-Landweber iteration with convex penalty terms of nonlinear ill-posed problems,Inverse Problems, 2023(with Ruixue Gu, Bo Han, Hongsun Fu) Heuristic rule for inexact Newton-Landweber iteration with convex penalty terms of nonlinear: ill-posed problems - IOPscience A Fast Data-Driven Iteratively Regularized Method with Convex Penalty for Solving Ill-Posed Problems，SIAM Journal on Imaging Sciences, 2023, (with Guangyu Gao, Bo Han and Shanshan Tong)A Fast Data-Driven Iteratively Regularized Method with Convex Penalty for Solving Ill-Posed Problems | SIAM Journal on Imaging Sciences Asymptotic solitons of the focusing Kundu-Eckhaus equation with time-periodic boundary condition,SCIENTIA SINICA Mathematica, 2023, (with Xiubin Wang, Yong Chen, Shoufu Tian, Jinjie Yang and Zhiqiang Li) Asymptotic solitons of the focusing Kundu-Eckhaus equation with time-periodic boundary condition (sciengine.com) Iterative Runge-Kutta-typemethods with convex penalty for inverse problems in Hilbert spaces, CSIAM Transaction on Applied Mathematics, 2022,( with Shanshan Tong, Wei Wang and Bo Han)Iterative Runge-Kutta-Type Methods with Convex Penalty for Inverse Problems in Hilbert Spaces (global-sci.org) Convergence analysis of inexact Newton-Landweber iteration under Holder stability, Inverse Problems, 2022, (with Yuxin Xia and Bo Han) Convergence analysis of inexact Newton–Landweber iteration under H？lder stability - IOPscience Two-point Landweber-type method with convex penalty terms for non-smooth nonlinear inverse problems, IMA Journal of Numerical Analysis, 2022, (with Wei Wang, Bo Han and Yong Chen)Two-point Landweber-type method with convex penalty terms for nonsmooth nonlinear inverse problems | IMA Journal of Numerical Analysis | Oxford Academic (oup.com) Levenberg–Marquardt method with general convex penalty for nonlinear inverse problems, Journal of Computational and Applied Mathematics, 2022, (with Bo Han and Yong Chen) Levenberg–Marquardt method with general convex penalty for nonlinear inverse problems - ScienceDirect Analysis of a generalized regularized Gauss-Newton method under heuristic rule in Banach spaces, Inverse Problems 2021, (with Yong Chen, Li Li and Bo Han) Analysis of a generalized regularized Gauss–Newton method under heuristic rule in Banach spaces - IOPscience An accelerated homotopy perturbation iteration for nonlinear ill-posed problems in Banach spaces with uniformly convex penalty, Inverse Problems, 2021, (with Yuxin Xia and Bo Han)An accelerated homotopy perturbation iteration for nonlinear ill-posed problems in Banach spaces with uniformly convex penalty - IOPscience REGINN-IT method with general convex penalty terms for nonlinear inverse problems, Applicable Analysis, 2021, (with Yong Chen and Bo Han) Full article: REGINN-IT method with general convex penalty terms for nonlinear inverse problems (tandfonline.com) A projected Bouligand-Landweber iteration for non-smooth ill-posed problems, Inverse Problems, 2021, (with Yong Chen and Bo Han) A projected Bouligand–Landweber iteration for non-smooth ill-posed problems - IOPscience Analysis of a heuristic rule for the IRGNM in Banach spaces with convex regularization terms, Inverse Problems, 2020 (with Qinain Jin, Zhengqiang Zhang, Bo Han and Yong Chen) Analysis of a heuristic rule for the IRGNM in Banach spaces with convex regularization terms - IOPscience