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钟敏
副教授
数学学院
计算数学系
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  • 1. 陈南,钟敏许伯熹,带正则化项的时间序列聚类算法及其应用,复旦学报(自然科学版),51(2012),56-63.

    2. Zhong M.,Lu S., Cheng J., Multiscale analysis for ill-posed problems with semi-discrete Tikhonov regularization, Inverse Problems, 28(6),2012,19-37.

    3. Zhong M., Loy R. J., Anderssen R. S., Approximating the Kohlrausch function by sums of exponentials, ANZIAM J, 54(04), 2013, 19-37.

    4. Jin Q., Zhong M.,On the iteratively regularized Gauss-Newton method in Banach spaces with applications to parameter identification problems, Numer.       Math., 124(4), 2013, 647-683.

    5. Xu B., Lu S., Zhong M., Multiscale support vector regression method in Sobolev spaces  on bounded domains,  Applicable Analysis,  94(3), 2014, 1-22. 

    6. Jin Q., Zhong M., Nonstationary iterated Tikhonov regularization in Banach spaces with general convex penalty term, Numer. Math., 127(3), 2014, 485-513. 

    7. Hon Y.C., Schaback R., Zhong M., The meshless kernel-based method of lines for parabolic equations, Comput. Math. Appl. 68(12), 2014, 2057-2067.


    8. Zhong M., Hon Y. C., Lu S., Multiscale support vector approach for solving ill-posed problems, J. Sci. Comput.64, 2015, 317-340.

    9. Zhong M., Wang W., A global minimization algorithm for Tikhonov functionals with p- convex(p>=2)penalty  terms in Banach spaces,   Inverse Problems, 32, 2016, 104008 (30pp).

    10. Zhong M., Liu J.J., On the reconstruction of media inhomogeneity by inverse wave  scattering model, Sci. China. Math., 60(10), 2017, 1825-1836.


    11.Zhong M., Le Gia Q.T., Wang W., A multiscale support vector regression method on spheres with data compression, Applicable Analysis, 98(8),2019,  1496-1519.

    12Zhong M., Wang W., A regularizing multilevel approach for nonlinear inverse problems,  Appl. Numer. Math.,135, 2019, 297-315.

    13Zhong M., Jin Q., Wang W., Regularization of inverse problems by two-point gradient methods in Banach spaces., Numer.Math, 143(3), 2019, 713-747.

    14.Zhong M., Wang W., The two-point gradient methods for nonlinear inverse problems based on Bregman projections., Inverse Problems, 2020,045012.

    15. Shao, N., Zhong, M., Yan, Y., Pan, H. S., Cheng J., Chen W.B., Dynamic models for Coronavirus Disease 2019 and da.ta analysis., Mathematical Methods in the Applied Sciences, 43(7),2020:4943-4949.

    16. Cheng J., Zhang J. T., Zhong M.  Extract the information from the big data from randomly distributed noise.  J. Inverse Ill-Posed Probl. 2021; 29(4): 525–541.

    17. Zhong M., Wang W., Tong S. S. An asymptotical regularization with convex constraints for inverse problems. Inverse Problems, 2022 (38):  045007 (30pp).

    18. Zhong M., Wang W., Zhu K.  On the asymptotical regularization with convex constraints for nonlinear ill-posed problems, Applied Mathematics Letters, 2022 (133): 108247.

    19 Zhong M.,  LeGia Q.T., Sloan I.H.  A multiscale RBF method for severely ill-posed problems on spheres. J. Sci. Comput., 2023, 94:22.

    20 Zhong M., Qiu L. Y., Wang W. Landweber-type method with uniformly convex constraints under conditional stability assumptions. Applied Mathematics Letters, 2023(144): 108723.

    21    21 Chen Y., Cheng J., Zhang J. T., Zhong M. A big data processing technique based on Tikhonov regularization. Practical Inverse Problems and Their Prospects. vHiSilicon (Shanghai) Technologies CO.,LIMITED. Shanghai, China. 

             22  Hu Y., Zhong M.(corresponding author) Semi-discrete Tikhonov regularization in RKHS with large randomly distributed noise. Inverse Problems 2023 (39) : 095005 (23pp).

        23 Zhong M., Li X. Y.,  and Liu X. M. Extract the information via multiple repeated observations under randomly distributed noise. JIIP 2023. online https://doi.org/10.1515/jiip-2022-0063.

    24.   24. Zhu K., Zhong M. (corresponding author) Solving the acousto-electric tomography by the adaptive Nesterov method of Kaczmarz type. Inverse Problems, 2025 (41) 035007 (19pp).













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  • 1. 国家自然科学基金青年项目,11501102,基于紧支径向基函数的支持向量机多尺度算法及其应用,2016/01-2019/0118万元,主持。

    2. 江苏省科技厅基础研究计划(自然科学基金)青年基金项目,BK20150594,球面上的多尺度正则化拟合算法及其数值实现 ,2015/07-2018/0620万元,主持。

    3. 国家自然科学基金面上项目,11871149,Banach空间基于光滑惩罚项的正则化算法及其应用,2019/01-2022/12,52万元,主持。

    3. 国家自然科学基金面上项目,带斜导数边界条件的偏微分方程定解问题的边界反演,2017/01-2020/12,48万元,参与。

    4. 国家自然科学基金面上项目,带有随机输入的偏微分方程反问题不确定性量化方法,2018/01-2021/12,48万元,参与。

    5. 国家自然科学基金专项项目,大气数据同化的高效数值算法及数学理论分析,2023/01/01-2026/12/31,参与。


    2019 东南大学至善青年学者

    2018 东南大学第25届授课竞赛二等奖,江苏省青蓝工程青年骨干教师

    2017 东南大学微课竞赛二等奖

    2016 上海市优秀博士学位论文

    2014 上海市优秀毕业生,第六届反问题理论与计算分析研讨会浪潮青年学术奖

    2012 中国计算数学协会优秀青年论文竞赛二等奖