Yang Liu
Orcid: 0000-0001-7300-9215Affiliations:
- Shenyang University of Technology, School of Electrical Engineering, Shenyang, China
- Northeastern University, College of Information Science and Engineering, Shenyang, China (PhD 2018)
According to our database1,
Yang Liu
authored at least 12 papers
between 2016 and 2024.
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Bibliography
2024
Rules Refine the Riddle: Global Explanation for Deep Learning-Based Anomaly Detection in Security Applications.
Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security, 2024
2021
Stochastic Stabilization for Discrete-Time Markovian Jump Systems With Time-Varying Delay and Two Markov Chains Under Partly Known Transition Probabilities.
IEEE Access, 2021
2020
Value Iteration-Based H<sub>∞</sub> Controller Design for Continuous-Time Nonlinear Systems Subject to Input Constraints.
IEEE Trans. Syst. Man Cybern. Syst., 2020
Data-Based Adaptive Dynamic Programming for a Class of Discrete-Time Systems With Multiple Delays.
IEEE Trans. Syst. Man Cybern. Syst., 2020
H<sub>∞</sub> Tracking Control of Discrete-Time System With Delays via Data-Based Adaptive Dynamic Programming.
IEEE Trans. Syst. Man Cybern. Syst., 2020
H<sub>∞</sub> Control for a Class of Discrete-Time Systems via Data-Based Policy Iteration With Application to Wind Turbine Control.
IEEE Access, 2020
Sliding Mode Control of One-Sided Lipschitz Nonlinear Markovian Jump Systems With Partially Unknown Transition Rates.
IEEE Access, 2020
2018
Data-driven optimal tracking control for discrete-time systems with delays using adaptive dynamic programming.
J. Frankl. Inst., 2018
Synchronization criterion of complex networks with time-delay under mixed topologies.
Neurocomputing, 2018
Neural network-based H<sub>∞</sub> sliding mode control for nonlinear systems with actuator faults and unmatched disturbances.
Neurocomputing, 2018
2017
Neural-network-based control scheme for a class of nonlinear systems with actuator faults via data-driven reinforcement learning method.
Neurocomputing, 2017
2016
ADP based optimal tracking control for a class of linear discrete-time system with multiple delays.
J. Frankl. Inst., 2016