中国地质大学主页平台管理系统 WM--英文主页--Paper Publications

吴敏

Doctoral Supervisor

Gender : Male
Date of Birth : 1963-07-01
Education Level : Doctoral Degree in Education
Degree : Doctoral degree
Status : 在岗
School/Department : 未来技术学院
Date of Employment : 2014-09-01

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Current position: 英文主页 >> Scientific Research >> Paper Publications

Paper Publications

[291] X. G. Liu, M. Wu, R. Martin, M. L. Tang. Stability analysis for neutral systems with mixed delays. Journal of Computational and Applied Mathematics, 2007, 202 (2): 478-497.
[292] Y. He, Q. G. Wang, C. Lin, M. Wu. Delay-range-dependent stability for systems with time-varying delay. Automatica, 2007, 43 (2): 371-376.
[293] Y. He, G. P. Liu, D. Rees, M. Wu. Stability analysis for neural networks with time-varying interval delay. IEEE Transactions on Neural Networks, 2007, 18 (6): 1850-1854.
[294] Y. He, G. P. Liu, D. Rees, M. Wu. Improved stabilisation method for networked control systems. IET Control Theory and Applications, 2007, 1 (6): 1580-1585.
[295] Y. He, G. P. Liu, D. Rees, M. Wu. Improved delay-dependent stability criteria for systems with nonlinear perturbations. European Journal of Control, 2007, 13 (4): 356-365.
[296] X. M. Zhang, M. Wu, Q. L. Han, J. H. She. A new integral inequality approach to delay-dependent robust H∞ control. Asian Journal of Control, 2006, 8 (2): 153-160.
[297] M. Wu, Y. He, J. H. She. Delay-dependent stabilization for systems with multiple unknown time-varying delays. International Journal of Control Automation and Systems, 2006, 4 (6): 682-688.
[298] Y. He, M. Wu, J. H. She. Delay-dependent exponential stability of delayed neural networks with time-varying delay. IEEE Transactions on Circuits and Systems II: Express Briefs, 2006, 53 (7): 553-557.
[299] Y. He, M. Wu, J. H. She. An improved global asymptotic stability criterion for delayed cellular neural networks. IEEE Transactions on Neural Networks, 2006, 17 (1): 250-252.
[300] Y. He, Q. G. Wang, M. Wu, C. Lin. Delay-dependent state estimation for delayed neural networks. IEEE Transactions on Neural Networks, 2006, 17 (4): 1077-1081.

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