甘敏 - 福州大学 - 数学与计算机科学学院

个人简介

个人简介甘敏，男，博士，教授，博导。2010年获中南大学控制科学与工程专业博士学位。2010年6月至2016年10月在合肥工业大学电气与自动化工程学院工作，2016年11月至今在福州大学数学与计算机科学学院工作。2011年7月至9月在香港城市大学系统工程与工程管理学院做研究助理工作，2013年4月至12月在澳门大学科技学院做博士后工作，2015年7月至2016年5月在美国达科他州大学做博士后工作。可招收计算机科学与技术专业博士生，计算机软件与理论、应用数学、运筹学与控制论、计算机应用，软件工程等方向的学术和专业型硕士研究生。目前我们在做计算机视觉中的超分辨率，图像处理的去模糊，机器学习中的稀疏主成分分析、低秩矩阵分解等问题。

研究领域

机器学习中的优化方法、计算机视觉、系统辨识、图像处理。

近期论文

查看导师最新文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

主要学术论文 [1]Feng Zhou, Min GAN (甘敏, 通讯作者), Han-Xiong Li. SD-ARX Modeling and Robust MPC with Variable Feedback Gain for Nonlinear Systems. Submitted to IET Control Theory & Applications. [2]Qiong-Ying Chen, Min GAN (甘敏, 通讯作者), C. L. Philip Chen. Variable projection approach based on BFGS algorithm for blind deconvolution, IET Image Processing， Major revision. [3]Jing Chen, Min GAN, C. L. Philip Chen. Robust standard gradient descent algorithm for ARX models using Aitken acceleration technique, IEEE Transactions on Cybernetics, Major revision. [4]Guang-Yong Chen, Shu-qiang Wang, Min GAN (甘敏, 通讯作者), C. L. Philip Chen. Insights into Algorithms of Separable Nonlinear Least Squares Problems. IEEE Transactions on Image Processing, Major revision [5]Shuqiang Wang, Min Gan, Han-Xiong Li, Yanyan Shen, Baiying Le. Image Classification using Optimized Projective Scheme under Tensor Mode. Submitted to IEEE Transactions on Cybernetics. [6]Genggeng Liu, Weida Zhu, Zhen Zhuang, Min Gan, Chi-Hua Chen, and Wenzhong Guo. A Robust Multilayer X-Architecture Global Routing System Based on Particle Swarm Optimization. IEEE Transactions on Systems, Man and Cybernetics: Systems, Major revision. [7]Jing Chen, Biao Huang, Min GAN, C. L. Philip Chen. Improved EM algorithms for time-delayed systems based on the gradient descent method and Arnoldi's method. Submitted to IEEE Transactions on Automatic Control. [9]Jing Chen, Biao Huang, Min GAN, C. L. Philip Chen. A novel reduced-order algorithm for rational models based on Arnoldi process and Krylov subspace. Automatica, Accept for publication. [10]Jian-nan Su, Min GAN (甘敏, 通讯作者), Guang-Yong Chen, C. L. Philip Chen. Attention-Based Convolutional Neural Networks for Image Super-Resolution. IEEE Transactions on Multimedia, Major revision. [11]Guang-Yong Chen, Min GAN (甘敏, 通讯作者), C. L. Philip Chen, Hong-Tao Zhu. Frequency Principle in Broad Learning System. IEEE Transactions on Neural Network and Learning Systems, Major revision. [12]Hong-Tao Zhu, Min GAN (甘敏, 通讯作者), Guang-Yong Chen, C. L. Philip Chen. An Iterative Implementation of Variable Projection Algorithm for Separable Nonlinear Optimization Problems. IEEE Transactions on Systems, Man and Cybernetics: Systems, Major revision. [13]Min GAN (甘敏), Yu Guan, Guang-Yong Chen, C. L. Philip Chen. Recursive Variable Projection Algorithm for a Class of Separable Nonlinear Models. IEEE Transactions on Neural Network and Learning Systems, in press, Doi: 10.1109/TNNLS.2020.3026482.. [14]Jia Chen, Min GAN (甘敏, 通讯作者), Guang-Yong Chen, C. L. Philip Chen. Constrained Variable Projection Optimization for a Stationary RBF-AR Model. IEEE Transactions on Systems, Man and Cybernetics: Systems, 2020, in press, DOI (identifier) 10.1109/TSMC.2020.3034644. [15]Min GAN (甘敏), Hong-Tao Zhu, Guang-Yong Chen, C. L. Philip Chen. Weighted Generalized Cross Validation Based Regularization for Broad Learning System. IEEE Transactions on Cybernetics, 2020, in press, DOI (identifier): 10.1109/TCYB.2020.3015749. [16]Feng Zhou, Min GAN (甘敏, 通讯作者), C. L. Philip Chen. State-dependent ARX Model-based RPC with Variable Feedback Control Laws for Output Tracking, IEEE Transactions on Industrial Electronics, 2020, accept for publication, in press, DOI (identifier) 10.1109/TIE.2020.2984440. [17] Shu-qiang Wang, Xiang-yu Wang, Yan-yan Shen, Zhi-le Yang, Min GAN (甘敏, 通讯作者), Bai-ying Lei. Diabetic Retinopathy Diagnosis using Multi-channel Generative Adversarial Network with Semi-supervision, IEEE Transactions on Automation Science and Engineering, 2020, accept for publication, in press, DOI (identifier) 10.1109/TASE.2020.2981637. [18]Guang-Yong Chen, Min GAN (甘敏, 通讯作者), C. L. Philip Chen, Han-Xiong Li. Basis Function Matrix based Flexible Coefficient Autoregressive Models: A Framework for Time Series and Nonlinear System Modeling. IEEE Transactions on Cybernetics, acceptable for publication, DOI (identifier) 10.1109/TCYB.2019.2900469, 2019, in press. [19]【book chapter】Shu-qiang Wang, Hong-fei Wang, Albert C. Cheung, Yan-yan Shen, Min GAN (甘敏, 通讯作者). Ensemble of 3D Densely Connected Convolutional Network for Diagnosis of Mild Cognitive Impairment and Alzheimer’s Disease. Deep Learning Applications，2020，Springer Nature Singapore Pte Ltd. [20]Dong-Qing Wang, Suo Zhang, Min GAN (甘敏), and Jian-long Qiu, "A novel EM identification method for Hammerstein systems with missing output data," IEEE Transactions on Industrial Informatics, 2020, 16(4): 2500-2508. [21]Min GAN (甘敏), Guang-Yong Chen, Long Chen, C. L. Philip Chen. Term selection for a class of nonlinear separable models. IEEE Transactions on Neural Networks and Learning Systems, 2020, 31(2): 445 - 451. [22] Tianjun Li, Long Chen, Min GAN. Quality control of imbalanced mass spectra from isotopic labeling experiments. BMC Bioinformatics, 2019.11.6, 20(1): 549. [23]Guang-Yong Chen, Shu-Qiang Wang, Dong-Qing Wang, Min GAN (甘敏, 通讯作者). Regularization Methods for Separable Nonlinear Models. Nonlinear Dynamics, 2019, 98: 1287–1298. [24]Min GAN (甘敏), Xiao-xian Chen, Ding Feng, Guang-Yong Chen, C. L. Philip Chen. Adaptive RBF-AR Models Based on Multi-innovation Least Squares Method. IEEE Signal Processing Letters, 2019, 26(8): 1182-1186. [25]Guang-Yong Chen, Min GAN (甘敏, 通讯作者), Feng Ding, C. L. Philip Chen. Modified Gram-Schmidt Method Based Variable Projection Algorithm for Separable Nonlinear Models. IEEE Transactions on Neural Networks and Learning System, 2019, 30(8): 2410-2418. (ESI高被引论文，hot topic论文) [26]Guang-Yong Chen, Min GAN (甘敏, 通讯作者), C. L. Philip Chen, Han-Xiong Li. A Regularized Variable Projection Algorithm for Separable Nonlinear Least Squares Problems. IEEE Transactions on Automatic Control, 2019, 64(2): 526 – 537.(长文，ESI高被引论文，hot topic论文) [27]Guang-Yong Chen, Min GAN (甘敏, 通讯作者), C. L. Philip Chen, Long Chen. A Two-Stage Estimation Algorithm Based on Variable Projection Method for GPS Positioning. IEEE Transactions on Instrumentation & Measurement, 2018, 67 (11): 2518 - 2525. [28]Min GAN (甘敏), C. L. Philip Chen, Guang-Yong Chen, Long Chen. On some separated algorithms for separable nonlinear squares problems [J]. IEEE Transactions on Cybernetics, 2018, 48(10): 2866-2874. (ESI高被引论文，hot topic论文) [29]Guang-Yong Chen, Min GAN (甘敏, 通讯作者). Generalized Exponential Autoregressive Models for Nonlinear Time Series: Stationarity, Estimation and Applications. Information Sciences, 2018，438：46-57. [30]Min Gan (甘敏), Long Chen, C. Y. Zhang, Hui Ping “A Self-Organizing State Space Type Microstructure Model for Financial Asset Allocation”. IEEE Access, 2016, 4: 8035-8043. [31]Min GAN(甘敏), C. L. Philip Chen, Long Chen, Chun-yang Zhang. Exploiting the Interpretability and Forecasting Ability of the RBF-AR Model for Nonlinear Time Series [J]. International Journal of Systems Science, 2016, 47(8): 1868-1876. [32]Min GAN(甘敏), Han-Xiong Li, C. L. Philip Chen, Long Chen. A Potential Method for Determining Nonlinearity in Wind Data [J], IEEE Power and Energy Technology Systems Journal, 2015, 2(2): 74-81. [33]Min GAN(甘敏), C. L. Philip Chen, Han-Xiong Li, Long Chen. Gradient radial basis function based varying-coefficient Autoregressive Model for nonlinear and nonstationary time series [J]. IEEE Signal Processing Letters, 2015, 22(7): 809-812. [34]Min GAN(甘敏), Han-Xiong Li, Hui Peng. A variable projection approach for efficient Estimation of RBF-ARX model [J]. IEEE Transactions on Cybernetics, 2015, 45(3): 476-485. [35]Chun-yang Zhang, C. L. Philip Chen, Long Chen, Min Gan(甘敏). Fuzzy Restricted Boltzmann Machine to Enhance Deep Learning [J]. IEEE Transactions on Fuzzy Systems, 2015, 23(6): 2163-2173. [36]Min GAN(甘敏), Han-xiong LI. An Efficient Variable Projection Formulation for Separable Nonlinear Least Squares Problems [J]. IEEE Transactions on Cybernetics, 2014, 44(5): 707-711. [37]Chun-yang Zhang, C. L. Philip Chen, Min Gan(甘敏). Predictive Deep Boltzmann Machine for Multi-Period Wind Speed forecasting [J]. IEEE Transactions on sustainable energy, 2015, 6(4): 1416-1425. [38]Min Gan(甘敏), Yu Cheng, Kai Liu, Gang-lin Zhang. Seasonal time series prediction based on a quasi-linear autoregressive model [J]. Applied Soft Computing, 2014, 24(1): 13-18. [39]Geng Zhang, Han-Xiong Li, Min GAN(甘敏). Design a Wind Speed Prediction Model Using Probabilistic Fuzzy System [J], IEEE Transactions on Industrial Informatics, 2012, 8(4): 819-827. [40]Min GAN(甘敏), Yun-zhi Huang, Ming Ding, Xue-ping Dong. Testing for nonlinearity in solar radiation time series by a fast method of surrogate data [J]. Solar Energy, 2012, 86(9): 2893-2896. [41]Min Gan(甘敏), Hui Peng, Liyuan Chen. A Global-local Approach to Parameter Optimization of RBF-type Models [J]. Information Sciences, 2012, 197(15): 144-160. [42]Min Gan(甘敏), Hui Peng, Xueping Dong. A hybrid algorithm to optimize RBF network architecture and parameters for nonlinear time series modeling [J]. Applied Mathematical Modelling, 2012, 36(7): 2911-2919. [43]Min Gan(甘敏), Hui Peng. Stability analysis of RBF-network based state-dependent autoregressive model for nonlinear time series [J]. Applied Soft Computing, 2012, 12(1): 174-181. [44]Min Gan(甘敏), Ming Ding, Yun-zhi Huang, Xueping Dong. The effect of different state sizes on Mycielski approach for wind speed prediction [J]. Journal of Wind Engineering & Industrial Aerodynamics, 2012, 109:89-93. [45]Min Gan(甘敏), Hui Peng, et al. A locally linear RBF network-based state-dependent AR model for nonlinear time series modeling [J]. Information Sciences, 2010, 180: 4370~4383. [46]Min Gan(甘敏), Hui Peng, et al. An Adaptive Decision Maker for Constrained Evolutionary Optimization [J]. Applied Mathematics and Computation, 2010, 215(12): 4172~4184. [47]甘敏，丁明，董学平. 基于改进的Mycielski方法的风速时间序列预测[J]. 系统工程理论与实践，2013, 33(4) : 1084-1088. [48]甘敏，彭辉，黄云志，董学平. 自组织状态空间模型参数初始分布搜索算法[J].自动化学报，2012, 38(9): 1538-1543. [49]甘敏，彭辉，陈晓红. 基于金融市场微结构模型和进化算法的动态资产分配[J].系统工程学报. 2011，26(3): 314-321. [50]甘敏，彭辉，陈晓红. RBF-AR模型在非线性时间序列预测中的应用[J].系统工程理论与实践. 2010，30(6)：1055~1061. [51]甘敏，彭辉，王勇. 多目标优化与适应惩罚的混合约束优化进化算法[J]. 控制与决策, 2010, 25(3): 378~382. [52]甘敏，彭辉.不同基函数对RBF-ARX 模型的影响研究[J].中南大学学报. 2010, 41(6): 2231~2235. [53]甘敏，彭辉. 基于带回归权重的RBF-AR模型的混沌时间序列预测[J]. 系统工程与电子技术， 2010，32(4)：820~824. [54]甘敏，彭辉. RBF神经网络参数优化的两种混合优化算法[J]. 控制与决策, 2009, 24(8): 1172~1176.