Nan Hou
Nan Hou
Northeast Petroleum University
Verified email at
Cited by
Cited by
Non-fragile state estimation for discrete Markovian jumping neural networks
N Hou, H Dong, Z Wang, W Ren, FE Alsaadi
Neurocomputing 179, 238-245, 2016
Robust partial-nodes-based state estimation for complex networks under deception attacks
N Hou, Z Wang, DWC Ho, H Dong
IEEE Transactions on Cybernetics, 2019
Variance-constrained state estimation for complex networks with randomly varying topologies
H Dong, N Hou, Z Wang, W Ren
IEEE transactions on neural networks and learning systems 29 (7), 2757-2768, 2017
Event-triggered distributed state estimation for a class of time-varying systems over sensor networks with redundant channels
H Dong, X Bu, N Hou, Y Liu, FE Alsaadi, T Hayat
Information Fusion 36, 243-250, 2017
Filter design, fault estimation and reliable control for networked time-varying systems: a survey
J Li, H Dong, F Han, N Hou, X Li
Systems Science & Control Engineering 5 (1), 331-341, 2017
Distributed filtering for time-varying systems over sensor networks with randomly switching topologies under the Round-Robin protocol
X Bu, H Dong, F Han, N Hou, G Li
Neurocomputing 346, 58-64, 2019
H∞ state estimation for discrete-time neural networks with distributed delays and randomly occurring uncertainties through fading channels
N Hou, H Dong, Z Wang, W Ren, FE Alsaadi
Neural Networks 89, 61-73, 2017
Finite‐horizon fault estimation under imperfect measurements and stochastic communication protocol: Dealing with finite‐time boundedness
H Dong, N Hou, Z Wang, H Liu
International Journal of Robust and Nonlinear Control 29 (1), 117-134, 2019
On passivity and robust passivity for discrete-time stochastic neural networks with randomly occurring mixed time delays
J Li, H Dong, Z Wang, N Hou, FE Alsaadi
Neural Computing and Applications 31 (1), 65-78, 2019
Event-triggered state estimation for time-delayed complex networks with gain variations based on partial nodes
N Hou, H Dong, W Zhang, Y Liu, FE Alsaadi
International Journal of General Systems 47 (5), 477-490, 2018
Event-triggered non-fragile H∞ fault detection for discrete time-delayed nonlinear systems with channel fadings
W Ren, S Sun, N Hou, C Kang
Journal of the Franklin Institute 355 (1), 436-457, 2018
Non-fragile H∞ filtering for nonlinear systems with randomly occurring gain variations and channel fadings
W Ren, N Hou, Q Wang, Y Lu, X Liu
Neurocomputing 156, 176-185, 2015
Dynamical performance analysis of communication-embedded neural networks: A survey
W Chen, D Ding, J Mao, H Liu, N Hou
Neurocomputing 346, 3-11, 2019
State estimation for discrete neural networks with randomly occurring uncertainties and missing measurements
N Hou, H Dong, X Bu, F Yang
2016 12th World Congress on Intelligent Control and Automation (WCICA), 875-880, 2016
Tobit Kalman filtering: Conditional expectation approach
F Han, H Dong, N Hou, X Bu
2017 Chinese Automation Congress (CAC), 928-932, 2017
State estimation for delayed Markovian jumping neural networks over sensor nonlinearities and disturbances
J Li, H Dong, F Han, N Hou
IECON 2017-43rd Annual Conference of the IEEE Industrial Electronics Society …, 2017
Distributed fault estimation for time-varying systems with randomly occurring nonlinearities over sensor networks
X Bu, H Dong, W Ren, L Yang, N Hou
2016 35th Chinese Control Conference (CCC), 7456-7461, 2016
The system can't perform the operation now. Try again later.
Articles 1–17