基本介紹
- 中文名：夏又生
- 國籍：中國
- 職業：教師
- 畢業院校：香港中文大學
基本信息,論文發表,教育經歷,研究領域,主持的項目,發表論文情況,
基本信息
| 職稱 | 教授 |
|---|---|
| 職務 | 博士生導師 |
| 主講課程 | 數值計算方法，人工神經網路，神經動力學最佳化算法及套用，神經計算原理及套用 |
| 研究方向 | 智慧型計算與模式識別 |
研究興趣:圖像配準與融合,盲圖像恢復與重建,圖像超分辨,隨機最佳化算法
論文發表
在國外重要核心學術刊物，如《Journal of Optimization Theory and Application》、《IEEE自動控制彙刊》、《IEEE圖像處理彙刊》、《IEEE信號處理彙刊》、《IEEE神經網路彙刊》、《IEEE機器人控制彙刊》、《IEEE電路與系統彙刊》、《IEEE系統、人與控制彙刊》、《國際神經網路協會會刊：神經網路》、《麻省理工學院會刊：神經計算》等著名SCI雜誌發表多篇學術論文，其中第一作者45餘篇，IEEE Transaction上 40篇。
1.系統參數辯識與語音增強研究工作
[1] 夏又生, Z.P. Deng，X. Zheng, Analysis and application of a novel fast algorithm for 2-D ARMA model parameter estimation, Automatica, vol. 49, pp 3056-3064, 2013.
[2] 夏又生, M. Kamel, and H. Leung ,A Fast Algorithm for AR Parameter Estimation Using A Novel Constrained Least Squares method，Neural Networks, vol. 33, pp. 396-405, 2010.
[3] 夏又生 M. Kamel, A generalized least absolute deviation method for parameter estimation of autoregressive signals, IEEE Transactions on Neural Networks,vol.19,107-118, 2008 .
[4] Y.S. Xia, L. Henry, and N. Xie ``A New Regression estimator with neural network realization", IEEE Transactions on Signal Processing, vol. 53, pp.672-685, 2005.
[5] 陳誌慶, 夏又生,A Fast Algorithm For Vector ARMA Parameter Estimation, International Conference on Electrical and Engineering and Automatic Control, vol. 3, pp178-181, Zibo, China, 2010.
[3] 夏又生 M. Kamel, A generalized least absolute deviation method for parameter estimation of autoregressive signals, IEEE Transactions on Neural Networks,vol.19,107-118, 2008 .
[4] Y.S. Xia, L. Henry, and N. Xie ``A New Regression estimator with neural network realization", IEEE Transactions on Signal Processing, vol. 53, pp.672-685, 2005.
[5] 陳誌慶, 夏又生,A Fast Algorithm For Vector ARMA Parameter Estimation, International Conference on Electrical and Engineering and Automatic Control, vol. 3, pp178-181, Zibo, China, 2010.
[6] 夏又生, 俞穎, Speech Enhancement Using Generalized Least Absolute Deviation Estimation，International Conference on Audio, Language and Image Processing，vol. 1, pp. 64-68, Shanghai, China， 2010 .
2. 數據融合研究工作:
[1] 夏又生 and H. Leung，Performance analysis of statistical optimal data fusion algorithms, Information Science, 2014.
[2] 夏又生 and H. Leung，A Fast Learning Algorithm for Blind Data Fusion Using A Novel L2-Norm Estimation，IEEE Sensors Journal, vol.14, pp. 666 – 672, 2014.
[3] 夏又生 M. Kamel, Cooperative learning algorithms for data fusion using novel L1 estimation, IEEE Transactions on Signal Processing, vol. 56, 1083-1095,2008 .
[4] 夏又生 and M. Kamel, A Measurement Fusion Method for Nonlinear System Identification and Its Cooperative Learning Algorithm , Neural Computation, Vol. 19, pp. 1589-1632, 2007.
[5] 夏又生, Leung H, Nonlinear spatial-temporal prediction based on optimal fusion, IEEE TRANSACTIONS ON NEURAL NETWORKS , vol. 17 , 975-988 Published: 2006
3. 圖像恢復與重建研究工作
[4] 夏又生 and M. Kamel, A Measurement Fusion Method for Nonlinear System Identification and Its Cooperative Learning Algorithm , Neural Computation, Vol. 19, pp. 1589-1632, 2007.
[5] 夏又生, Leung H, Nonlinear spatial-temporal prediction based on optimal fusion, IEEE TRANSACTIONS ON NEURAL NETWORKS , vol. 17 , 975-988 Published: 2006
3. 圖像恢復與重建研究工作
[1] 夏又生，Sun C., and Zheng WX, A Discrete-Time Neural Network for Fast Solving Large Linear L1-norm Estimation Problems and its Application to Image Restoration, IEEE Transactions on Neural Networks and Learning Systems, vol.23 , pp. 812 - 820 , 2012
[2] 石泉斌，夏又生*，Fast multi-channel image reconstruction using a novel two-dimensional algorithm, Multimedia Tools and Applications , vol. 63, Feb, 2013 online Published。
[3] 夏又生, Z.P. Deng，X. Zheng, Analysis and application of a novel fast algorithm for 2-D ARMA model parameter estimation, Automatica, vol. 49, pp 3056-3064, 2013.
[4] 夏又生 and M. Kamel, Novel cooperative neural fusion algorithms for image restoration and image fusion, IEEE Transactions on Image Processing, vol. 16, pp. 367-381, 2007 .
[5] 夏又生, A fast algorithm for constrained GLAD estimation with application to image restoration, Proceeding of World Congress on Intelligent Control
and Automation, July, Jinan, China, pp.729-734,2010.
[6] 莊金蓮,夏又生, An Improved Regularization Approach for Blind Restoration of multichannel Imagery，International Congress on Image and Signal Processing，上海，2011年10月。
[7] 文虎兒， 夏又生, A SIFT operator -based Image Registration Using Cross-Correlation Coefficient, International Congress on Image and Signal Processing，上海，2011年10月。
[5] 夏又生, A fast algorithm for constrained GLAD estimation with application to image restoration, Proceeding of World Congress on Intelligent Control
and Automation, July, Jinan, China, pp.729-734,2010.
[6] 莊金蓮,夏又生, An Improved Regularization Approach for Blind Restoration of multichannel Imagery，International Congress on Image and Signal Processing，上海，2011年10月。
[7] 文虎兒， 夏又生, A SIFT operator -based Image Registration Using Cross-Correlation Coefficient, International Congress on Image and Signal Processing，上海，2011年10月。
4．智慧型最佳化算法的研究工作
[1] 夏又生， 陳天平，J. Shan，A novel iteration method for computing generalized inverse，Neural Computation, vol.26, pp. 449-465 , 2014
[2] 夏又生, A Compact Cooperative Recurrent Neural Network for Computing General Constrained L-1 Norm Estimators，IEEE Transactions on Signal Processing， vol.57, pp. 3693-3697,2009。
[3] 夏又生, G. Feng, and J. Wang, ``A novel recurrent neural network for solving nonlinear optimization problems with inequality constraints”, IEEE Transactions on Neural Networks, vol.19,1340-1353, 2008
[3] 夏又生, G. Feng, and J. Wang, ``A novel recurrent neural network for solving nonlinear optimization problems with inequality constraints”, IEEE Transactions on Neural Networks, vol.19,1340-1353, 2008
[4] 夏又生and M. Kamel, ``Cooperative Recurrent Neural Networks for solving L1 estimation problems with general linear constraints," Neural Computation, vol. 20, pp.844-872, 2008.
[5] 夏又生, New cooperative recurrent neural networks for solving constrained variational inequality problems， Science in China: Information sciences, vol.52, 1766-177, 2009.
[5] 夏又生, New cooperative recurrent neural networks for solving constrained variational inequality problems， Science in China: Information sciences, vol.52, 1766-177, 2009.
[6] Sun C., 夏又生, An analysis of a neural dynamical approach to solving optimization Problems，IEEE Transactions on Automatic Control,vol. 54, pp. 1972-1977,2009.
[7] 夏又生and G. Feng, ``A New Neural Network for Solving
Nonlinear Projection equations," Neural Networks, vol. 20, pp. 577-589, 2007.
[8] 夏又生, G. Feng, and M. S Kamel, Development and analysis of neural dynamical approaches to solving nonlinear programming problems, IEEE Transactions on Automatic Control, Vol 52, pp. 2154-2159, 2007.
[9] 夏又生, G. Feng, and J. Wang, ``A Primal-Dual Neural Network
for On-Line Resolving Constrained Kinematic Redundancy," IEEE Transactions on Systems, Man and Cybernetics - Part B, vol. 35, pp. 54-64, 2005.
[10] 夏又生, ``An extended projection neural network for constrained optimization", Neural Computation, vol. 16, no. 4, pp. 863-883, 2004.
[11] 夏又生, ``Further results on global convergence and stability of globally projected dynamical systems," Journal of Optimization Theory and Applications, vol. 122, pp.627-149, 2004.
Nonlinear Projection equations," Neural Networks, vol. 20, pp. 577-589, 2007.
[8] 夏又生, G. Feng, and M. S Kamel, Development and analysis of neural dynamical approaches to solving nonlinear programming problems, IEEE Transactions on Automatic Control, Vol 52, pp. 2154-2159, 2007.
[9] 夏又生, G. Feng, and J. Wang, ``A Primal-Dual Neural Network
for On-Line Resolving Constrained Kinematic Redundancy," IEEE Transactions on Systems, Man and Cybernetics - Part B, vol. 35, pp. 54-64, 2005.
[10] 夏又生, ``An extended projection neural network for constrained optimization", Neural Computation, vol. 16, no. 4, pp. 863-883, 2004.
[11] 夏又生, ``Further results on global convergence and stability of globally projected dynamical systems," Journal of Optimization Theory and Applications, vol. 122, pp.627-149, 2004.
[12] 夏又生 and F. Gang, ``On Convergence Rate of Projection Neural
Networks," IEEE Transactions on Automatic Control, vol.
49, pp. 91-96, 2004.
Networks," IEEE Transactions on Automatic Control, vol.
49, pp. 91-96, 2004.
[13] 夏又生and J. Wang, ``A General Projection neural network for solving monotone variational inequality and related optimization problems", IEEE Transactions Neural Networks}, vol.15, pp. 318-328, 2004.
[14] 夏又生,J. Wang, and L. M. Fork, ``Grasping Force Optimization for Multifingered Robotic Hands Using a Recurrent Neural Network," IEEE Transactions on Robotics and Automation, vol. 20, pp. 549-554, 2004.
教育經歷
1982 南京大學理學學士
1989 南京大學計算數學碩士學位
2000 香港中文大學自動化和計算機輔助工程博士學位
加拿大卡爾加里大學博士後
香港中文大學博士後
香港城市大學博士後
加拿大滑鐵盧大學的智慧型實驗室研究員
研究領域
知識系統
圖像處理與分析
機器的感知和感測器
自治系統
模式分析與識別
約束最佳化神經網路的設計與分析及它們的工程套用
主持的項目
主持完成省部級基金項目和國際合作子項目多項。現主持國家自然科學科學基金面上項目和福建省自然科學基金項目各一項。
發表論文情況
在國外重要核心學術刊物，如《Journal of Optimization Theory and Application》、《IEEE自動控制彙刊》、《IEEE圖像處理彙刊》、《IEEE信號處理彙刊》、《IEEE神經網路彙刊》、《IEEE機器人控制彙刊》、《IEEE電路與系統彙刊》、《IEEE系統、人與控制彙刊》、《國際神經網路協會會刊：神經網路》、《麻省理工學院會刊：神經計算》等著名SCI雜誌發表多篇學術論文，其中第一作者45餘篇，IEEE Transaction上 40篇。
