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华中科技大学人工智能与自动化学院导师教师师资介绍简介-曾志刚

本站小编 Free考研考试/2021-07-25


曾志刚 职称:教授、博士生导师
电话:
邮箱:zgzeng@hust.edu.cn
研究方向:切换系统控制理论与应用、计算智能、系统稳定性等
个人主页:http://aia.hust.edu.cn/zhigangzeng/




个人简介

















个人简介
1989—1993年,湖北师范学院,数学,获学士学位;
1993—1996年,湖北大学,生态数学,获硕士学位;
2000—2003年,华中科技大学,系统分析与集成,获博士学位。

主要研究方向
切换系统控制理论与应用;计算智能;系统稳定性;联想记忆。

招生要求
专业需求:控制科学与工程,数学,计算机科学与技术等
招生方向:复杂系统理论方法及应用;系统建模、仿真与优化

代表性成果及获奖情况
[1] Zhigang Zeng, Wei Xing Zheng, “Multistability of neural networks with time-varying delays and concave-convex characteristics,” IEEE Transactions on Neural Networks and Learning Systems, Vol. 23, No. 2, pp. 293-305, 2012.
[2] Zhigang Zeng, Tingwen Huang and Wei Xing Zheng, “Multistability of recurrent neural networks with time-varying delays and the piecewise linear activation function,” IEEE Transactions on Neural Networks, Vol.21, No.8, pp.1371-1377, 2010.
[3] Zhigang Zeng, Jun Wang, “Associative memories based on continuous-time cellular neural networks designed using space-invariant cloning templates,” Neural Networks, Vol.22, pp.651-657, 2009.
[4] Zhigang Zeng, Jun Wang, “Design and analysis of high-capacity associative memories based on a class of discrete-time recurrent neural networks,” IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, Vol.38, No.6, pp.1525-1536, 2008.
[5] Zhigang Zeng, Jun Wang, “Analysis and design of associative memories based on recurrent neural networks with linear saturation activation functions and time-varying delays,” Neural Computation, Vol.19, No.8, pp.2149-2182, 2007.
[6] Zhigang Zeng, Jun Wang, “Global exponential stability of recurrent neural networks with time-varying delays in the presence of strong external stimuli,” Neural Networks, Vol.19, No.10, pp.1528-1537, 2006.
[7] Zhigang Zeng, Jun Wang, “Multiperiodicity of discrete-time delayed neural networks evoked by periodic external inputs,” IEEE Transactions on Neural Networks,(Regular Paper), Vol.17, No.5, pp.1141-1151, 2006.
[8] Zhigang Zeng, Jun Wang, “Improved conditions for global exponential stability of recurrent neural networks with time-varying delays,” IEEE Transactions on Neural Networks, (Regular Paper), Vol.17, No.3, pp.623-635, 2006.
[9] Zhigang Zeng, Jun Wang, “Complete stability of cellular neural networks with time-varying delays,” IEEE Transactions on Circuits and Systems-I: Regular Papers, Vol.53, No.4, pp.944-955, 2006.
[10] Zhigang Zeng, Jun Wang, “Multiperiodicity and exponential attractivity evoked by periodic external inputs in delayed cellular neural networks,” Neural Computation, Vol.18,No.4, pp.848-870, 2006.
[11] Zhigang Zeng, Jun Wang and Xiaoxin Liao, “Global asymptotic stability and global exponential stability of neural networks with unbounded time-varying delays,” IEEE Transactions on Circuits and Systems II, Express Briefs, Vol.52, No.3, pp.168-173, 2005.
[12] Zhigang Zeng, Jun Wang and Xiaoxin Liao, “Stability analysis of delayed cellular neural networks described using cloning templates,” IEEE Transactions on Circuits and Systems-I: Fundamental Theory and Applications, Vol.51, No.11, pp.2313-2324, 2004.
[13] Zhigang Zeng, Jun Wang and Xiaoxin Liao, “Global exponential stability of neural networks with time-varying delays,” IEEE Transactions on Circuits and Systems-I: Fundamental Theory and Applications, Vol.50, No.10, pp.1353-1358, 2003.





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