张浩
硕士生导师
教师姓名：张浩
教师拼音名称：zhanghao
性别：男
职称：副教授
在职信息：在职
学历：博士研究生毕业
学位：工学博士学位
办公地点：逸夫楼C606
电子邮箱：
毕业院校：华中科技大学
所属院系：信息学院
所在单位：信息学院
其他联系方式
暂无内容
论文成果
- [8] Zhang Hao and Zeng Zhigang, “Synchronization of recurrent neural networks with unbounded delays and time-varying coefficients via generalized differential inequalities,” Neural Networks, vol. 143, pp. 161-170, 2021. (SCI, 中科院二区).
- [7] Zhang Hao, Yufeng Zhou, and Zeng Zhigang, “Master-slave synchronization of neural networks with unbounded delays via adaptive method,” IEEE Transactions on Cybernetics, DOI: 10.1109/TCYB.2022.3168090, 2022. (SCI, 中科院一区).
- [6] Zhang Hao and Zeng Zhigang, “Adaptive synchronization of reaction-diffusion neural networks with nondifferentiable delay via state coupling and spatial coupling,” IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2022.3144222, 2022. (SCI, 中科院一区).
- [5] Zhang Hao and Zeng Zhigang, “Stability and synchronization of nonautonomous reaction-diffusion neural networks with general time-varying delays,” IEEE Transactions on Neural Networks and Learning Systems, vol. 33, no. 10, pp. 5804-5817, 2022. (SCI, 中科院一区).
- [4] Zhang Hao and Zeng Zhigang, “Synchronization of non-identical neural networks with unknown parameters and diffusion effects via robust adaptive control techniques,” IEEE Transactions on Cybernetics, vol. 51, no. 2, pp. 660-672, 2021. (SCI, 中科院一区).
- [3] Zhang Hao, Pal Nikhil R., Sheng Yin, and Zeng Zhigang, “Distributed adaptive tracking synchronization for coupled reaction-diffusion neural network,” IEEE Transactions on Neural Networks and Learning Systems, vol. 30, no. 5, pp. 1462-1475, 2019. (SCI, 中科院一区).
- [2] Zhang Hao, Zeng Zhigang, and Han Qing-Long, “Synchronization of multiple reaction-diffusion neural networks with heterogeneous and unbounded time-varying delays,” IEEE Transactions on Cybernetics, vol. 49, no. 8, pp. 2980-2991, 2019. (SCI, 中科院一区).
- [1] Zhang Hao, Sheng Yin, and Zeng Zhigang, “Synchronization of coupled reaction-diffusion neural networks with directed topology via an adaptive approach,” IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 5, pp. 1550-1561, 2018. (SCI, 中科院一区).
