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Qingshan Liu 0002
Person information
- affiliation: Huazhong University of Science and Technology, School of Automation, Wuhan, China
- affiliation: Southeast University, School of Automation, Nanjing, China
Other persons with the same name
- Qingshan Liu — disambiguation page
- Qingshan Liu 0001 — Nanjing University of Information Science & Technology (NUIST), School of Information and Control (and 1 more)
- Qingshan Liu 0003 — Chinese University of Hong Kong, Hong Kong
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2020 – today
- 2024
- [j62]Yuanyuan Yue, Qingshan Liu:
Distributed dual consensus algorithm for time-varying optimization with coupled equality constraint. Appl. Math. Comput. 474: 128712 (2024) - [j61]Han-Yu Wu, Qingshan Liu:
Event-triggered secure consensus for second-order nonlinear multiagent systems against asynchronous DoS attacks. J. Frankl. Inst. 361(14): 107065 (2024) - [j60]Jinming Li, Qingshan Liu, Guoyi Chi:
Distributed deep reinforcement learning based on bi-objective framework for multi-robot formation. Neural Networks 171: 61-72 (2024) - [j59]Haitao Wang, Qingshan Liu, Chentao Xu:
Predefined-time distributed optimization and anti-disturbance control for nonlinear multi-agent system with neural network estimator: A hierarchical framework. Neural Networks 175: 106270 (2024) - [j58]Yanling Zheng, Qingshan Liu, Jun Wang:
A Specified-Time Convergent Multiagent System for Distributed Optimization With a Time-Varying Objective Function. IEEE Trans. Autom. Control. 69(2): 1257-1264 (2024) - [j57]Youshen Xia, Qingshan Liu, Jun Wang, Andrzej Cichocki:
A Survey of Neurodynamic Optimization. IEEE Trans. Emerg. Top. Comput. Intell. 8(4): 2677-2696 (2024) - [j56]Kaixuan Li, Qilong Hu, Qingshan Liu, Zhigang Zeng, Fan Cheng:
A Predefined-Time Consensus Algorithm of Multi-Agent System for Distributed Constrained Optimization. IEEE Trans. Netw. Sci. Eng. 11(1): 957-968 (2024) - [j55]Qingshan Liu, Yuanyuan Yue:
Distributed Multiagent System for Time-Varying Quadratic Programming With Application to Target Encirclement of Multirobot System. IEEE Trans. Syst. Man Cybern. Syst. 54(9): 5339-5351 (2024) - 2023
- [j54]Jun Zhu, Qingshan Liu, Chentao Xu:
Graph Convolutional Neural Network with Multi-Scale Attention Mechanism for EEG-Based Motion Imagery Classification. Int. J. Pattern Recognit. Artif. Intell. 37(14): 2354020:1-2354020:19 (2023) - [j53]Chentao Xu, Qingshan Liu:
A resilient distributed optimization algorithm based on consensus of multi-agent system against two attack scenarios. J. Frankl. Inst. 360(12): 9096-9114 (2023) - [j52]Kaixuan Li, Qingshan Liu, Zhigang Zeng:
Multiagent System With Periodic and Event-Triggered Communications for Solving Distributed Resource Allocation Problem. IEEE Trans. Syst. Man Cybern. Syst. 53(10): 6245-6256 (2023) - [c19]Xiwang Meng, Qingshan Liu, Jiang Xiong:
An Accelerated Gradient Tracking Algorithm with Projection Error for Distributed Optimization. ICACI 2023: 1-6 - 2022
- [j51]Chentao Xu, Qingshan Liu:
A Median-based Resilient Distributed Optimization Algorithm Against Byzantine Attack. Int. J. Artif. Intell. Tools 31(6): 2240020:1-2240020:17 (2022) - [j50]Qingshan Liu, Zhigang Zeng, Yaochu Jin:
Distributed machine learning, optimization and applications. Neurocomputing 489: 486-487 (2022) - [j49]Chentao Xu, Qingshan Liu, Tingwen Huang:
Resilient Penalty Function Method for Distributed Constrained Optimization under Byzantine Attack. Inf. Sci. 596: 362-379 (2022) - [j48]Hanjie Liu, Jinren Zhang, Qingshan Liu, Jinde Cao:
Minimum spanning tree based graph neural network for emotion classification using EEG. Neural Networks 145: 308-318 (2022) - [j47]Chentao Xu, Qingshan Liu:
An inertial neural network approach for robust time-of-arrival localization considering clock asynchronization. Neural Networks 146: 98-106 (2022) - [j46]Chentao Xu, Miao Wang, Guoyi Chi, Qingshan Liu:
An inertial neural network approach for loco-manipulation trajectory tracking of mobile robot with redundant manipulator. Neural Networks 155: 215-223 (2022) - 2021
- [j45]Kaixuan Li, Qingshan Liu, Zhigang Zeng:
Quantized event-triggered communication based multi-agent system for distributed resource allocation optimization. Inf. Sci. 577: 336-352 (2021) - [j44]Qingshan Liu, Xinyi Le, Kaixuan Li:
A Distributed Optimization Algorithm Based on Multiagent Network for Economic Dispatch With Region Partitioning. IEEE Trans. Cybern. 51(5): 2466-2475 (2021) - [j43]Dongdong Yue, Jinde Cao, Qi Li, Qingshan Liu:
Neural-Network-Based Fully Distributed Adaptive Consensus for a Class of Uncertain Multiagent Systems. IEEE Trans. Neural Networks Learn. Syst. 32(7): 2965-2977 (2021) - [j42]Shaosheng Xu, Jinde Cao, Qingshan Liu, Leszek Rutkowski:
Optimal Control on Finite-Time Consensus of the Leader-Following Stochastic Multiagent System With Heuristic Method. IEEE Trans. Syst. Man Cybern. Syst. 51(6): 3617-3628 (2021) - 2020
- [j41]Zilin Gao, Jiang Xiong, Jing Zhong, Fuming Liu, Qingshan Liu:
Adaptive State Observer Design for Dynamic Links in Complex Dynamical Networks. Comput. Intell. Neurosci. 2020: 8846438:1-8846438:8 (2020) - [j40]Qun Huang, Jinde Cao, Qingshan Liu:
Synchronization of Delayed Inertial Cohen-Grossberg Neural Networks Under Adaptive Feedback Controller. Int. J. Comput. Intell. Syst. 13(1): 472-478 (2020) - [j39]Yan Zhao, Qingshan Liu:
A consensus algorithm based on collective neurodynamic system for distributed optimization with linear and bound constraints. Neural Networks 122: 144-151 (2020) - [j38]Xingchen Xu, Qingshan Liu, Chuanlin Zhang, Zhigang Zeng:
Prescribed Performance Controller Design for DC Converter System With Constant Power Loads in DC Microgrid. IEEE Trans. Syst. Man Cybern. Syst. 50(11): 4339-4348 (2020) - [j37]Kaixuan Li, Qingshan Liu, Shaofu Yang, Jinde Cao, Guoping Lu:
Cooperative Optimization of Dual Multiagent System for Optimal Resource Allocation. IEEE Trans. Syst. Man Cybern. Syst. 50(11): 4676-4687 (2020)
2010 – 2019
- 2019
- [j36]Yan Zhao, Qingshan Liu:
A Lagrange Multiplier Method for Distributed Optimization Based on Multi-Agent Network With Private and Shared Information. IEEE Access 7: 83297-83305 (2019) - [j35]Shaofu Yang, Jun Wang, Qingshan Liu:
Cooperative-Competitive Multiagent Systems for Distributed Minimax Optimization Subject to Bounded Constraints. IEEE Trans. Autom. Control. 64(4): 1358-1372 (2019) - [j34]Shaofu Yang, Jun Wang, Qingshan Liu:
Consensus of Heterogeneous Nonlinear Multiagent Systems With Duplex Control Laws. IEEE Trans. Autom. Control. 64(12): 5140-5147 (2019) - [j33]Bingrong Xu, Qingshan Liu, Tingwen Huang:
A Discrete-Time Projection Neural Network for Sparse Signal Reconstruction With Application to Face Recognition. IEEE Trans. Neural Networks Learn. Syst. 30(1): 151-162 (2019) - [c18]Qingshan Liu, Jiang Xiong, Shaofu Yang:
Mixed-Norm Projection-Based Iterative Algorithm for Face Recognition. ISNN (2) 2019: 331-340 - 2018
- [j32]Bingrong Xu, Qingshan Liu:
Iterative projection based sparse reconstruction for face recognition. Neurocomputing 284: 99-106 (2018) - [j31]Yan Zhao, Qingshan Liu:
A Continuous-Time Distributed Algorithm for Solving a Class of Decomposable Nonconvex Quadratic Programming. J. Artif. Intell. Soft Comput. Res. 8(4): 283-291 (2018) - [j30]Shaofu Yang, Qingshan Liu, Jun Wang:
A Collaborative Neurodynamic Approach to Multiple-Objective Distributed Optimization. IEEE Trans. Neural Networks Learn. Syst. 29(4): 981-992 (2018) - [c17]Qingshan Liu, Jiang Xiong, Jing Zhong, Hong Ying, Kaixuan Li:
A Distributed Algorithm Based on Multi-agent Network for Solving Linear Algebraic Equation. ISNN 2018: 415-422 - 2017
- [j29]Sabri Arik, Qingshan Liu, Weng Kin Lai:
SI: ICONIP 2015: Learning algorithms and classification systems. Neurocomputing 248: 1-2 (2017) - [j28]Shaofu Yang, Qingshan Liu, Jun Wang:
A Multi-Agent System With a Proportional-Integral Protocol for Distributed Constrained Optimization. IEEE Trans. Autom. Control. 62(7): 3461-3467 (2017) - [j27]Qingshan Liu, Shaofu Yang, Yiguang Hong:
Constrained Consensus Algorithms With Fixed Step Size for Distributed Convex Optimization Over Multiagent Networks. IEEE Trans. Autom. Control. 62(8): 4259-4265 (2017) - [j26]Qingshan Liu, Shaofu Yang, Jun Wang:
A Collective Neurodynamic Approach to Distributed Constrained Optimization. IEEE Trans. Neural Networks Learn. Syst. 28(8): 1747-1758 (2017) - [j25]Shaofu Yang, Qingshan Liu, Jun Wang:
Distributed Optimization Based on a Multiagent System in the Presence of Communication Delays. IEEE Trans. Syst. Man Cybern. Syst. 47(5): 717-728 (2017) - [c16]Bingrong Xu, Qingshan Liu:
Elastic Net Based Weighted Iterative Method for Image Classification. ICONIP (6) 2017: 481-489 - [c15]Jian Shang, Qingshan Liu:
Cognitive Load Recognition Using Multi-threshold United Complex Network. ICONIP (6) 2017: 490-498 - [c14]Qingshan Liu, Kaixuan Li:
A continuous-time algorithm based on multi-agent system for distributed least absolute deviation subject to hybrid constraints. IECON 2017: 7381-7386 - [c13]Jian Shang, Wei Zhang, Jiang Xiong, Qingshan Liu:
Cognitive Load Recognition Using Multi-channel Complex Network Method. ISNN (1) 2017: 466-474 - 2016
- [j24]Qingshan Liu, Jun Wang, Zhigang Zeng:
Advances in Neural Networks, Intelligent Control and Information Processing. Neurocomputing 198: 1-3 (2016) - [j23]Qingshan Liu, Jun Wang:
L1-Minimization Algorithms for Sparse Signal Reconstruction Based on a Projection Neural Network. IEEE Trans. Neural Networks Learn. Syst. 27(3): 698-707 (2016) - [c12]Shaofu Yang, Jun Wang, Qingshan Liu:
Multiple-objective optimization based on a two-time-scale neurodynamic system. ICACI 2016: 193-199 - 2015
- [j22]Qingshan Liu, Jun Wang:
A Second-Order Multi-Agent Network for Bound-Constrained Distributed Optimization. IEEE Trans. Autom. Control. 60(12): 3310-3315 (2015) - [j21]Qingshan Liu, Jun Wang:
A Projection Neural Network for Constrained Quadratic Minimax Optimization. IEEE Trans. Neural Networks Learn. Syst. 26(11): 2891-2900 (2015) - [c11]Qingshan Liu, Yan Zhao, Long Cheng:
Continuous-Time Multi-agent Network for Distributed Least Absolute Deviation. ISNN 2015: 436-443 - [e4]Sabri Arik, Tingwen Huang, Weng Kin Lai, Qingshan Liu:
Neural Information Processing - 22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015, Proceedings, Part I. Lecture Notes in Computer Science 9489, Springer 2015, ISBN 978-3-319-26531-5 [contents] - [e3]Sabri Arik, Tingwen Huang, Weng Kin Lai, Qingshan Liu:
Neural Information Processing - 22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015, Proceedings, Part II. Lecture Notes in Computer Science 9490, Springer 2015, ISBN 978-3-319-26534-6 [contents] - [e2]Sabri Arik, Tingwen Huang, Weng Kin Lai, Qingshan Liu:
Neural Information Processing - 22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015, Proceedings, Part III. Lecture Notes in Computer Science 9491, Springer 2015, ISBN 978-3-319-26554-4 [contents] - [e1]Sabri Arik, Tingwen Huang, Weng Kin Lai, Qingshan Liu:
Neural Information Processing - 22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015, Proceedings, Part IV. Lecture Notes in Computer Science 9492, Springer 2015, ISBN 978-3-319-26560-5 [contents] - 2014
- [j20]Jinde Cao, Qingshan Liu, Sabri Arik, Jianlong Qiu, Haijun Jiang, Ahmed M. Elaiw:
Computational Neuroscience. Comput. Math. Methods Medicine 2014: 120280:1-120280:2 (2014) - [j19]Qingshan Liu, Tingwen Huang, Jun Wang:
One-Layer Continuous-and Discrete-Time Projection Neural Networks for Solving Variational Inequalities and Related Optimization Problems. IEEE Trans. Neural Networks Learn. Syst. 25(7): 1308-1318 (2014) - 2013
- [j18]Qingshan Liu, Tingwen Huang:
A neural network with a single recurrent unit for associative memories based on linear optimization. Neurocomputing 118: 263-267 (2013) - [j17]Qingshan Liu, Chuangyin Dang, Tingwen Huang:
A One-Layer Recurrent Neural Network for Real-Time Portfolio Optimization With Probability Criterion. IEEE Trans. Cybern. 43(1): 14-23 (2013) - [j16]Qingshan Liu, Jun Wang:
A One-Layer Projection Neural Network for Nonsmooth Optimization Subject to Linear Equalities and Bound Constraints. IEEE Trans. Neural Networks Learn. Syst. 24(5): 812-824 (2013) - [c10]Qingshan Liu, Yan Zhao:
A continuous-time recurrent neural network for real-time support vector regression. CICA 2013: 189-193 - 2012
- [j15]Jinde Cao, Jianquan Lu, Jinling Liang, Qingshan Liu:
Preface. Math. Comput. Simul. 86: 1 (2012) - [j14]Yan Zhao, Qingshan Liu:
Generalized recurrent neural network for ϵ-insensitive support vector regression. Math. Comput. Simul. 86: 2-9 (2012) - [j13]Qingshan Liu, Zhishan Guo, Jun Wang:
A one-layer recurrent neural network for constrained pseudoconvex optimization and its application for dynamic portfolio optimization. Neural Networks 26: 99-109 (2012) - 2011
- [j12]Qingshan Liu, Jinde Cao:
Global exponential stability of discrete-time recurrent neural network for solving quadratic programming problems subject to linear constraints. Neurocomputing 74(17): 3494-3501 (2011) - [j11]Qingshan Liu, Jun Wang:
Finite-Time Convergent Recurrent Neural Network With a Hard-Limiting Activation Function for Constrained Optimization With Piecewise-Linear Objective Functions. IEEE Trans. Neural Networks 22(4): 601-613 (2011) - [j10]Zhishan Guo, Qingshan Liu, Jun Wang:
A One-Layer Recurrent Neural Network for Pseudoconvex Optimization Subject to Linear Equality Constraints. IEEE Trans. Neural Networks 22(12): 1892-1900 (2011) - [j9]Qingshan Liu, Jun Wang:
A One-Layer Recurrent Neural Network for Constrained Nonsmooth Optimization. IEEE Trans. Syst. Man Cybern. Part B 41(5): 1323-1333 (2011) - [c9]Qingshan Liu, Jun Wang:
A One-Layer Dual Recurrent Neural Network with a Heaviside Step Activation Function for Linear Programming with Its Linear Assignment Application. ICANN (2) 2011: 253-260 - [c8]Qingshan Liu, Jun Wang:
A one-layer recurrent neural network for constrained single-ratio linear fractional programming. ISCAS 2011: 1089-1092 - [p1]Qingshan Liu, Jun Wang:
Recurrent Neural Networks with Discontinuous Activation Functions for Convex Optimization. Integration of Swarm Intelligence and Artificial Neural Network 2011: 95-120 - 2010
- [j8]Qingshan Liu, Jinde Cao, Guanrong Chen:
A Novel Recurrent Neural Network with Finite-Time Convergence for Linear Programming. Neural Comput. 22(11): 2962-2978 (2010) - [j7]Qingshan Liu, Chuangyin Dang, Jinde Cao:
A novel recurrent neural network with one neuron and finite-time convergence for k-winners-take-all operation. IEEE Trans. Neural Networks 21(7): 1140-1148 (2010) - [j6]Qingshan Liu, Jinde Cao:
A Recurrent Neural Network Based on Projection Operator for Extended General Variational Inequalities. IEEE Trans. Syst. Man Cybern. Part B 40(3): 928-938 (2010) - [c7]Qingshan Liu, Jun Wang:
A One-Layer Dual Neural Network with a Unipolar Hard-Limiting Activation Function for Shortest-Path Routing. ICANN (2) 2010: 498-505
2000 – 2009
- 2009
- [c6]Qingshan Liu, Jinde Cao, Jinling Liang:
A Discrete-Time Recurrent Neural Network with One Neuron for k-Winners-Take-All Operation. ISNN (1) 2009: 272-278 - 2008
- [j5]Qingshan Liu, Jun Wang:
A One-Layer Recurrent Neural Network with a Discontinuous Activation Function for Linear Programming. Neural Comput. 20(5): 1366-1383 (2008) - [j4]Qingshan Liu, Jun Wang:
Two k-winners-take-all networks with discontinuous activation functions. Neural Networks 21(2-3): 406-413 (2008) - [j3]Qingshan Liu, Jun Wang:
A One-Layer Recurrent Neural Network With a Discontinuous Hard-Limiting Activation Function for Quadratic Programming. IEEE Trans. Neural Networks 19(4): 558-570 (2008) - [c5]Qingshan Liu, Jun Wang:
A One-Layer Recurrent Neural Network for Non-smooth Convex Optimization Subject to Linear Equality Constraints. ICONIP (2) 2008: 1003-1010 - [c4]Qingshan Liu, Jun Wang:
A one-layer recurrentneural network for convex programming. IJCNN 2008: 83-90 - 2007
- [c3]Qingshan Liu, Jun Wang:
A One-layer Recurrent Neural Network with a Unipolar Hard-limiting Activation Function for k-Winners-Take-All Operation. IJCNN 2007: 84-89 - 2006
- [j2]Qingshan Liu, Jinde Cao:
Improved global exponential stability criteria of cellular neural networks with time-varying delays. Math. Comput. Model. 43(3-4): 423-432 (2006) - [c2]Qingshan Liu, Jun Wang:
A Recurrent Neural Network for Non-smooth Convex Programming Subject to Linear Equality and Bound Constraints. ICONIP (2) 2006: 1004-1013 - [c1]Qingshan Liu, Jun Wang, Jinde Cao:
A Delayed Lagrangian Network for Solving Quadratic Programming Problems with Equality Constraints. ISNN (1) 2006: 369-378 - 2005
- [j1]Qingshan Liu, Jinde Cao, Youshen Xia:
A delayed neural network for solving linear projection equations and its analysis. IEEE Trans. Neural Networks 16(4): 834-843 (2005)
Coauthor Index
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last updated on 2024-10-16 20:30 CEST by the dblp team
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