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陈光永

来源:     发布日期:2022-09-17    浏览次数:

基本信息

职称 教授

职务 博士生导师

研究方向: 机器学习、计算机视觉、系统辨识

办公室:计算机学院4号楼126

电子邮件: gychen@fzu.edu.cn; cgykeda@mail.ustc.edu.cn.

联系电话: 185****3946

       陈光永,1989年生,男,博士,研究员,博士生导师,福州大学旗山学者。主要研究方向为:计算机视觉、智能医学图像分析机器学习优化方法、系统辨识等。主持科研项目3项,包括国家自然科学基金面上项目1项、福建省自然科学基金面上项目1项。以第一/通讯作者在国际知名刊物ieee tac、tpami、tip、tnnls、tim等上发表论文四十余篇。


科研项目:

[1] 国家自然科学基金面上项目,62173091,一类非线性模型的在线变量投影算法及其应用研究,2022/01-2025/12, 58万元,在研,主持。

[2] 福建省自然科学基金面上项目,2023j01130035, 2023/01-2015/12, 10万元, 在研,主持。

[3] 福州大学旗山学者科研项目,gxrc-22014,2022/01-2025/12,30万元,在研,主持。


近五年发表的部分代表性论文

[1] guang-yong chen陈光永, xiang-xiang su; min gan; wenzhong guo; c. l. philip chen; robust variable projection algorithm for the identification of separable nonlinear models, ieee transactions on automatic control, 2024, in press. doi: 10.1109/tac.2024.3376315(中科院一区sci期刊论文,自动化领域旗舰刊物,if: 6.8)

[2] guang-yong chen陈光永, min gan, jing chen, and long chen. embedded point iteration based recursive algorithm for online identification of nonlinear regression models. ieee transactions on automatic control, 2023, 68(7): 4257-4264. 中科院一区sci期刊论文,自动化领域旗舰刊物,if: 6.8

[3] jian-nan su, min gan, guang-yong chen (陈光永,通讯作者), jia-li yin, and c. l. philip chen. global learnable attention for single image super-resolution. ieee transactions on pattern analysis and machine intelligence, 2023, 45(7): 8453-8465. (中科院一区sci期刊论文,ccf-a期刊,if: 23.6)

[4] guang-yong chen(陈光永), wu-ding weng, jian-nan su, min gan, cl philip chen. dynamic degradation intensity estimation for adaptive blind super-resolution: a novel approach and benchmark dataset. ieee transactions on circuits and systems for video technology, 2023, in press. doi: . (中科院一sci期刊论文,if: 8.4)

[5] jian-nan su, min gan, guang-yong chen(陈光永, 通讯作者), wenzhong guo, cl philip chen. .ieee transactions on image processing, 2023, in press. doi: . (中科院一sci期刊论文,ccf-a,if: 10.6)

[6] guang-yong chen(陈光永), hui-lang xu, min gan, c. l. philip chen. a variable projection-based algorithm for fault detection and diagnosis. ieee transactions on instrumentation and measurement, 2023, in press. doi: 10.1109/tim.2023.3298636. (中科院二区sci期刊论文,if:5.6)

[7] guang-yong chen(陈光永),min gan, and c. l. philip chen. online identification of nonlinear system with separable structure. ieee transactions on neural networks and learning systems, 2022, in press. doi:10.1109/tnnls.2022.3215756. (中科院一区sci期刊论文,if: 14.255)

[8] guang-yong chen(陈光永), min gan, c. l. philip chen, hong-tao zhu, and long chen. frequency principle in broad learning system. ieee transactions on neural networks and learning systems, 2022, 33(11): 6983-6989中科院一区sci期刊论文,if: 14.255

[9] guang-yong chen (陈光永), min gan, hong-tao zhu, long chen, c. l. philip chen. an iterative implementation of variable projection for separable nonlinear optimization problems. ieee transactions on system, man, and cybernetics: systems, 2022, 52(11): 7259-7267. (中科院一区sci期刊论文,if: 13.451)

[10] min gan, hong-tao zhu, guang-yong chen (陈光永,通讯作者), c. l. philip chen. weighted generalized cross validation based regularization for broad learning system. ieee transactions on cybernetics, 2022, 52(5): 4064-4072. (中科院一区sci期刊论文,if: 11.448)

[11] long chen, jia-bing chen, guang-yong chen (陈光永,通讯作者), min gan, and c. l. philip chen. nuisance parameter estimation algorithms for separable nonlinear models. ieee transactions on system, man, and cybernetics: systems, 2022, 52(11): 7236-7247. (中科院一区sci期刊论文,if: 13.451) 

[12] jia chen, min gan, guang-yong chen (陈光永,通讯作者), c. l. philip chen. constrained variable projection optimization for stationary rbf-ar models. ieee transactions on systems, man, and cybernetics: systems, 202252(3): 1882-1890. (中科院一区sci期刊论文,if: 13.451)

[13] guang-yong chen (陈光永), min gan, c. l. philip chen, and han-xiong li. basis function matrix based flexible coefficient autoregressive models: a framework for time series and nonlinear system modeling.ieee transactions on cybernetics, 2021, 51(2): 614-623. 中科院一区sci期刊论文,if: 11.448

[14] guang-yong chen (陈光永), min gan, shu-qiang wang, and c. l. philip chen. insights into algorithms for separable nonlinear least squares problems. ieee transactions on image processing, 2021, 30: 1207-1218.  (中科院一区sci期刊论文,ccf-a期刊,if: 9.34)

[15] min gan, yu guan, guang-yong chen (陈光永,通讯作者), c. l. philip chen. recursive variable projection algorithm for a class of separable nonlinear models. ieee transactions on neural network and learning systems, 2021, 32(11): 4971 - 4982. (中科院一区sci期刊论文,if: 10.451)

[16] min gan, guang-yong chen (陈光永,通讯作者), long chen, c. l. philip chen. term selection for a class of separable nonlinear models. ieee transactions on neural networks and learning systems. 2020, 31(2), 445-451.中科院一区sci期刊论文,if: 10.451

[17] guang-yong chen(陈光永), min gan, feng ding, c. l. philip chen. modified gram-schmidt method-based variable projection algorithm for separable nonlinear problems. ieee transactions on neural networks and learning systems, 2019, 30(8): 2410-2418.中科院一区sci期刊论文,if: 10.451

[18]  guang-yong chen(陈光永), min gan, c. l. philip chen, han-xiong li. a regularized variable projection algorithm for separable nonlinear least squares problems. ieee transactions on automatic control2019, 64(2): 526-537. (中科院一区sci期刊论文,自动化领域旗舰刊物,if: 6.8)

[19] min gan, xiao xian chen, feng ding, guang-yong chen (陈光永,通讯作者), and c. l. philip chen. adaptive rbf-ar models based on multi-innovation least squares method. ieee signal processing letters, 2019, 26(8): 1182-1186. (中科院二区sci期刊论文,if: 3.9)

[20] min gan, guang-yong chen (陈光永,通讯作者), and c. l. philip chen. on some separated algorithms for separable nonlinear least squares problems. ieee transactions on cybernetics, 2019, 48(10): 2866-2874.(中科院一区sci期刊论文, if: 11.448)









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