2015 - SPIE Fellow
Zhanshan Wang mainly investigates Control theory, Artificial neural network, Exponential stability, Linear matrix inequality and Recurrent neural network. His Control theory study combines topics in areas such as Upper and lower bounds and Interval. The concepts of his Artificial neural network study are interwoven with issues in Stability, Discrete time and continuous time, Control theory, Mathematical optimization and Stability conditions.
Zhanshan Wang works mostly in the field of Exponential stability, limiting it down to topics relating to Applied mathematics and, in certain cases, Structure and Cellular neural network. In his research, Uniqueness is intimately related to Equilibrium point, which falls under the overarching field of Linear matrix inequality. His Recurrent neural network research is multidisciplinary, relying on both Content-addressable memory, Lyapunov function and Multistability.
His primary areas of study are Control theory, Artificial neural network, Exponential stability, Linear matrix inequality and Stability. His work in Control theory tackles topics such as Interval which are related to areas like Fuzzy logic. His Artificial neural network research incorporates elements of State, Discrete time and continuous time, Lyapunov function, Mathematical optimization and Applied mathematics.
His Exponential stability research includes elements of Equilibrium point, Recurrent neural network, Cellular neural network and Uniqueness. He combines topics linked to Lyapunov stability with his work on Linear matrix inequality. His Stability research focuses on Stability criterion and how it connects with Multiple integral.
His scientific interests lie mostly in Control theory, Artificial neural network, Control theory, Applied mathematics and Fuzzy control system. Particularly relevant to Stability is his body of work in Control theory. His study looks at the intersection of Artificial neural network and topics like State with Activation function.
His studies in Control theory integrate themes in fields like Trajectory and Synchronization. His research integrates issues of Markovian jump, Derivative and Differential equation in his study of Applied mathematics. His Fuzzy control system research also works with subjects such as
His primary scientific interests are in Control theory, Artificial neural network, Applied mathematics, Control theory and Fuzzy logic. The study incorporates disciplines such as Initial value problem, Interval and Multiple integral in addition to Control theory. His studies deal with areas such as Control system and Upper and lower bounds as well as Interval.
In his study, Polynomial and Stability criterion is strongly linked to Stability, which falls under the umbrella field of Multiple integral. Zhanshan Wang interconnects State and Inequality in the investigation of issues within Applied mathematics. Within one scientific family, Zhanshan Wang focuses on topics pertaining to Nonlinear system under Fuzzy logic, and may sometimes address concerns connected to Instability and Bounded function.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
A Comprehensive Review of Stability Analysis of Continuous-Time Recurrent Neural Networks
Huaguang Zhang;Zhanshan Wang;Derong Liu.
IEEE Transactions on Neural Networks (2014)
Novel Weighting-Delay-Based Stability Criteria for Recurrent Neural Networks With Time-Varying Delay
Huaguang Zhang;Zhenwei Liu;Guang-Bin Huang;Zhanshan Wang.
IEEE Transactions on Neural Networks (2010)
Global Asymptotic Stability of Recurrent Neural Networks With Multiple Time-Varying Delays
Huaguang Zhang;Zhanshan Wang;Derong Liu.
IEEE Transactions on Neural Networks (2008)
Adaptive Fault-Tolerant Tracking Control for MIMO Discrete-Time Systems via Reinforcement Learning Algorithm With Less Learning Parameters
Lei Liu;Zhanshan Wang;Huaguang Zhang.
IEEE Transactions on Automation Science and Engineering (2017)
Global Asymptotic Stability of Reaction–Diffusion Cohen–Grossberg Neural Networks With Continuously Distributed Delays
Zhanshan Wang;Huaguang Zhang.
IEEE Transactions on Neural Networks (2010)
LMI-Based Approach for Global Asymptotic Stability Analysis of Recurrent Neural Networks with Various Delays and Structures
Zhanshan Wang;Huaguang Zhang;Bin Jiang.
IEEE Transactions on Neural Networks (2011)
Data-Core-Based Fuzzy Min–Max Neural Network for Pattern Classification
Huaguang Zhang;Jinhai Liu;Dazhong Ma;Zhanshan Wang.
IEEE Transactions on Neural Networks (2011)
Barrier Lyapunov Function-Based Adaptive Fuzzy FTC for Switched Systems and Its Applications to Resistance–Inductance–Capacitance Circuit System
Lei Liu;Yan-Jun Liu;Dapeng Li;Shaocheng Tong.
IEEE Transactions on Systems, Man, and Cybernetics (2020)
Exponential Stability and Stabilization of Delayed Memristive Neural Networks Based on Quadratic Convex Combination Method
Zhanshan Wang;Sanbo Ding;Zhanjun Huang;Huaguang Zhang.
IEEE Transactions on Neural Networks (2016)
Stability Criteria for Recurrent Neural Networks With Time-Varying Delay Based on Secondary Delay Partitioning Method
Zhanshan Wang;Lei Liu;Qi-He Shan;Huaguang Zhang.
IEEE Transactions on Neural Networks (2015)
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