语音增强：福州大学数学与计算机科学学院导师介绍：夏又生

姓名：夏又生
性别：男
职称：教授
学院：数学与计算机科学学院
研究方向：智能计算与模式识别
联系电话：***********，*************

个人简历：

夏又生，男，2000年获香港中文大学计算智能专业博士学位。2000至2007年在香港和加拿大著名大学的计算智能实验室和机器学习与模式识别实验室做博士后和研究员。2007年作为特聘教授引入福州大学。现任软件工程系主任，博士生导师（应用数学专业，通信与信息系统专业）。从事智能优化算法和数字语音信号与图像处理研究，目前主要工作包括：首次提出了三大类神经动力学优化方法并在弱的条件下建立了方法理论；提出了一个广义约束最小绝对偏差估计方法和一个燥声约束的估计方法，改进了经典的二阶统计和高阶统计方法；提出了一个图像恢复的融合方法，克服了传统的正则化方法中最优参数选择的困难，提高了图像恢复效果。

讲授课程

本科生：数值计算方法，人工神经网络等

硕士生：神经动力学优化算法及应用，神经计算原理及应用

主持科研项目

(1) 基于广义约束最小绝对偏差估计的盲图像恢复神经网络算法,国家自然科学基金面上项目，2009.1-2011.12。

(2) 有色噪声下基于噪声约束最小均方估计的语音增强算法, 国家自然科学基金面上项目，2012.1-2015.12。

获奖

基于优化的非线性系统智能建模与控制，2010年高等学校科学研究优秀成果奖自然科学奖二等奖（排名第二）

近期主要论文

1. 盲系统参数估计方法及在语音增强应用的研究工作

[1]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.

[2] 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 .

[3] 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.

[4] 夏又生, 俞颖, Speech Enhancement Using Generalized Least Absolute Deviation Estimation，International Conference on Audio, Language and Image Processing，vol. 1, pp. 64-68, Shanghai, China， 2010 .

[5] 邓治坡,夏又生, A Fast Algorithm for 2-D ARMA Parameters Estimation，ADVANCES IN NEURAL NETWORKS ，Vol.5552, 276-286,2009.

[6] 陈志庆, 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.

2. 信号与图像去噪与融合的研究工作:

[1]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 .

[2] 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.

[3] 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. 图像恢复,图像配准的研究工作

[1] 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 .

[2] 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.

[3] 庄金莲,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。

[4] 文虎儿， 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．智能优化算法的研究工作:

[1] 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。

[2] Y.S. Xia and M. Kamel, ``Cooperative Recurrent Neural Networks for solving L1 estimation problems with general linear constraints," Neural Computation, vol. 20, pp.844-872, 2008.


[3] 夏又生, New cooperative recurrent neural networks for solving constrained variational inequality problems，中国科学F辑: 信息科学，英文版, vol.52, 1766-177, 2009.

[4] 夏又生 and G. Feng, ``A New Neural Network for Solving
Nonlinear Projection equations," Neural Networks, vol. 20, pp. 577-589, 2007.

[5] 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.

[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, 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.

[8]夏又生, ``An extended projection neural network for constrained optimization", Neural Computation, vol. 16, no. 4, pp. 863-883, 2004.

[9] 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.