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刘庆山

职称:教授

电话:027-87543630

邮箱:qsliu@hust.edu.cn

研究方向:计算智能理论与应用、神经网络、非线性系统理论等

个人主页:http://202.114.20.58:2006/qsliu.html

个人简介

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个人简介

2013.052013.07,美国德克萨斯A&M大学卡塔尔分校,科学系,访问学者

2010.022010.08,香港中文大学,机械与自动化工程学系,博士后

2009.082009.11,香港城市大学,制造工程及工程管理学系,高级研究员

2005.082008.07,香港中文大学,机械与自动化工程学系,哲学博士

2002.092005.03,东南大学,数学系,理学硕士

1997.092001.06,安徽师范大学,数学与计算机科学学院,理学学士

 

主要研究方向

计算智能理论与应用,神经网络,非线性系统理论,多智能体优化,模式识别与智能系统

 

学术任职

2012–2014, Neural Networks编委

2012, Cognitive Computation客座编委

2010, Mathematics and Computers in Simulation客座编委

 

代表性论文

[1]            Q. Liu, T. Huang, and J. Wang, “One-layer continuous- and discrete-time projection neural networks for solving variational inequalities and related optimization problems,” IEEE Transactions on Neural Networks and Learning Systems, 2014, in press.

[2]            Q. Liu and J. Wang, “A one-layer projection neural network for nonsmooth optimization subject to linear equalities and bound constraints,” IEEE Transactions on Neural Networks and Learning Systems, vol. 24, no. 5, pp. 812–824, May 2013.

[3]            Q. Liu, C. Dang, and T. Huang, “A one-layer recurrent neural network for real-time portfolio optimization with probability criterion,” IEEE Transactions on Cybernetics, vol. 43, no. 1, pp. 14–23, Feb. 2013.

[4]            Q. Liu, Z. Guo, and J. Wang, “A one-layer recurrent neural network for constrained pseudoconvex optimization and its application for dynamic portfolio optimization,” Neural Networks, vol. 26, pp. 99–109, Feb. 2012.

[5]            Q. Liu and J. Wang, “A one-layer recurrent neural network for constrained nonsmooth optimization,” IEEE Transactions on Systems, Man and Cybernetics-Part B: Cybernetics, vol. 41, pp. 1323–1333, Oct. 2011.

[6]            Q. Liu and J. Wang, “Finite-time convergent recurrent neural network with a hard-limiting activation function for constrained optimization with piecewise-linear objective functions,”IEEE Transactions on Neural Networks, vol. 22, pp. 601–613, Apr. 2011.

[7]            Z. Guo, Q. Liu, and J. Wang, “A one-layer recurrent neural network for pseudoconvex optimization subject to linear equality constraints,” IEEE Transactions on Neural Networks, vol. 22, pp. 1892–1900, Dec. 2011.

[8]            Q. Liu, C. Dang, and J. Cao, “A novel recurrent neural network with one neuron and finite-time convergence for k-winners-take-all operation,” IEEE Transactions on Neural Networks, vol. 21, pp. 1140–1148, July 2010.

[9]            Q. Liu and J. Cao, “A recurrent neural network based on projection operator for extended general variational inequalities,” IEEE Transactions on Systems, Man and Cybernetics-Part B: Cybernetics, vol. 40, pp. 928–938, June 2010.

[10]        Q. Liu, J. Cao, and G. Chen, “A novel recurrent neural network with finite-time convergence for linear programming,” Neural Computation, vol. 22, no. 11, pp. 2962–2978, 2010.

[11]        Q. Liu and J. Wang, “A one-layer recurrent neural network with a discontinuous hard-limiting activation function for quadratic programming,” IEEE Transactions on Neural Networks, vol. 19, pp. 558–570, Apr. 2008.
Outstanding Paper Award, IEEE Transactions on Neural Networks, 2011.

[12]        Q. Liu and J. Wang, “Two k-winners-take-all networks with discontinuous activation functions,” Neural Networks, vol. 21, no. 2-3, pp. 406–413, 2008.

[13]        Q. Liu and J. Wang, “A one-layer recurrent neural network with a discontinuous activation function for linear programming,” Neural Computation, vol. 20, no. 5, pp. 1366–1383, 2008.

[14]        Q. Liu, J. Cao, and Y. Xia, “A delayed neural network for solving linear projection equations and its analysis,” IEEE Transactions on Neural Networks, vol. 16, pp. 834–843, July 2005.

[15]        Q. Liu and J. Cao, “Invariant set and attractor of nonautonomous functional differential systems: a decomposition approach,” Nonlinear Dynamics, vol. 37, no. 1, pp. 19–29, 2004.

 

奖励与荣誉

[1]              2012,教育部“新世纪优秀人才支持计划”

[2]              2012,亚太神经网络联合会青年研究者奖

[3]              2011,教育部自然科学奖一等奖(排名第二)

[4]              2011IEEE计算智能学会神经网络汇刊杰出论文奖

[5]              2009,“SCOPUS寻找未来科学之星”信息领域“青年科学之星”奖

[6]              2006,江苏省优秀硕士学位论文