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姓名:黄鹤

学位:博士

毕业院校:香港城市大学

电子邮箱:hhuang@suda.edu.cn

办公地址:电子楼315

联系电话:

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个人简介

黄鹤,毕业于香港城市大学,获哲学博士学位。现为苏州大学电子信息学院教授,多次受邀到香港城市大学和德州农机大学卡塔尔分校进行合作研究。主持完成国家自然科学基金2项,江苏省自然科学基金面上项目2项,入选2016年度江苏高校“青蓝工程”优秀青年骨干教师培养对象。曾获教育部自然科学奖二等奖1项(排名第4),在科学出版社出版专著1部,在国际期刊如IEEE Transacitons on Neural Networks and Learning Systems, IEEE Transactions on Cybernetics, IEEE Transactions on Circuits and Systems: Part I, IEEE Transactions on Circuits and Systems: Part II, Neural Networks及国内外学术会议上发表学术论文90余篇,授权发明专利7项。受邀担任《新一代信息技术》,Neurocomputing, Circuits, Systems, & Signal Processin以及Neural Processing Letters的编委副主编。指导的研究生获2017年中国电子学会优秀硕士论文奖和2018年江苏省优秀学术学位硕士学位论文奖。

教育经历

  • 博士,2006-2009,香港城市大学

工作经历

  • 2009.9-至今,苏州大学电子信息学院
  • 2003.4-2006.10,东南大学计算机科学与工程学院

社会职务

1. Editorial member: Neurocomputing

2. Associate editor: Circuits, Systems & Signal Processing

3. Associate editor: Neural Processing Letters

4. 编委:新一代信息技术


研究领域

1. 神经网络学习算法

2. 深度学习

3. 优化算法

4. 模式识别

5. 图像处理


社会职务

1. Editorial member: Neurocomputing

2. Associate editor: Circuits, Systems & Signal Processing

3. Associate editor: Neural Processing Letters

4. 编委:新一代信息技术


开授课程

  • 1、数值最优化理论,研究生
  • 2、人工神经网络理论,研究生
  • 3、信号与系统,本科生
  • 4、工程数学(复变),本科生
  • 5、数值分析,本科生

科研项目

论文

  • 1、Zhongying Dong and He Huang, “A training algorithm with selectable search direction for complex-valued feedforward neural networks,” Neural Networks, vol. 137, pp. 75-84, 2021.
  • 2、Yongliang Zhang and He Huang, “Adaptive complex-valued stepsize based fast learning of complex-valued neural networks,” Neural Networks, vol. 124, pp. 233-242, April 2020.
  • 3、He Huang, Tingwen Huang and Yang Cao, “Reduced-order filtering of delayed static neural networks with Markovian jumping parameters,” IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no.11, pp. 5606-5618, 2018.
  • 4、He Huang, Tingwen Huang and Xiaoping Chen, “Reduced-order state estimation of delayed recurrent neural networks,” Neural Networks, vol. 98, pp. 59-64, 2018.
  • 5、Xusheng Qian, He Huang*, Xiaoping Chen and Tingwen Huang, “Efficient construction of sparse radial basis function neural networks using L1-regularization,” Neural Networks, vol. 94, pp. 239-254, 2017.
  • 6、Xusheng Qian, He Huang*, Xiaoping Chen and Tingwen Huang, “Generalized hybrid constructive learning algorithm for multioutput RBF networks,” IEEE Transactions on Cybernetics, vol. 47, no. 11, pp. 3634-3648, November, 2017.
  • 7、Jinxiang Zha, He Huang* and Yujie Liu, “A novel window function for memristor model with application in programming analog circuits,” IEEE Transactions on Circuits and Systems Part II, vol. 63, no. 5, pp. 423-427, May 2016.
  • 8、He Huang, Tingwen Huang and Xiaoping Chen, “Further result on guaranteed H∞ performance state estimation of delayed static neural networks,” IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 6, pp. 1335-1341, June 2015.
  • 9、He Huang, Tingwen Huang, Xiaoping Chen and Chunjiang Qian, “Exponential stabilization of delayed recurrent neural networks: A state estimation based approach,” Neural Networks, vol. 48, pp. 153-157, December 2013.
  • 10、He Huang, Tingwen Huang and Xiaoping Chen, “A mode-dependent approach to state estimation of recurrent neural networks with Markovian jumping parameters and mixed delays,” Neural Networks, vol. 46, pp. 50-61, October 2013.
  • 11、He Huang, Tingwen Huang and Xiaoping Chen, “Guaranteed H∞ performance state estimation of delayed static neural networks,” IEEE Transactions on Circuits and Systems Part II, vol. 60, no. 6, pp. 371-375, June 2013.
  • 12、He Huang, Tingwen Huang and Xiaoping Chen, “Global exponential estimates of delayed stochastic neural networks with Markovian switching,” Neural Networks, vol. 36, no. 1, pp. 136-145, December 2012.
  • 13、He Huang, Gang Feng and Xiaoping Chen, “Stability and stabilization of Markovian jump systems with time delay via new Lyapunov functionals,” IEEE Transactions on Circuits and Systems Part I: Regular Papers, vol. 59, no. 10, pp. 2413-2421, October, 2012.
  • 14、He Huang, Gang Feng and Jinde Cao, “State estimation for static neural networks with time-varying delay,” Neural Networks, vol. 23, no. 10, pp. 1202-1207, December 2010.
  • 15、He Huang and Gang Feng, “A scaling parameter approach to delay-dependent state estimation of delayed neural networks,” IEEE Transactions on Circuits and Systems Part II, vol. 57, no. 1, pp. 36-40, January 2010.
  • 16、He Huang and Gang Feng, “Delay-dependent H∞ and generalized H2 filtering for delayed neural networks”, IEEE Transactions on Circuits and Systems Part I: Regular Papers, vol. 56, no. 4, pp. 846-857, April 2009.
  • 17、He Huang, Gang Feng and Jinde Cao, “Robust state estimation for uncertain neural networks with time-varying delay”, IEEE Transactions on Neural Networks, vol. 19, no. 8, pp. 1329-1339, August 2008.
  • 18、He Huang and Gang Feng, “Synchronization of nonidentical chaotic neural networks with time delays,” Neural Networks, vol. 22, pp. 869-874, September 2009.

科技成果

软件著作
  • 1、时滞递归神经网络的状态估计理论与应用,2014,科学出版社
专利
  • 1、黄鹤、黄迎,基于深度学习的人脸特征点检测方法,2021
  • 2、黄鹤、韩子阳,基于生成对抗网络的多姿态面部表情识别方法,2020
  • 3、黄鹤、王健霖,基于深度学习的一阶段车牌检测识别方法,2020
  • 4、黄鹤、刘宇杰,一种基于简化卷积神经网络的车牌自动识别系统,2018
  • 5、黄鹤、张永亮、沈纲祥, 复值信道均衡器的设计方法, 2021

荣誉及奖励

  • 1、2017年度中国电子学会优秀硕士学位论文指导老师
  • 2、2018年度江苏省优秀学术学位硕士学位论文指导老师
  • 3、神经网络模型的动态特征及优化计算理论,2008,教育部自然科学奖二等奖

招生信息

欢迎电子信息、计算机、自动化和应用数学等专业的同学报考研究生,有兴趣的同学请通过电子邮件联系。