The scientist’s investigation covers issues in Control theory, Artificial neural network, Stability, Nonlinear system and Linear matrix inequality. Control theory is closely attributed to Chaotic in his research. His Artificial neural network study combines topics from a wide range of disciplines, such as Stability, Estimator, Mathematical optimization and Positive-definite matrix.
Shouming Zhong interconnects Quadratic equation, Type and Linear matrix in the investigation of issues within Mathematical optimization. His studies deal with areas such as Nonlinear perturbations, Numerical stability, Zero and Stochastic neural network as well as Stability. His research investigates the connection between Activation function and topics such as Finite time that intersect with problems in Bounded function, Interval and Applied mathematics.
His primary scientific interests are in Control theory, Artificial neural network, Exponential stability, Stability and Linear matrix inequality. His studies in Control theory, Linear matrix, Nonlinear system, Stability and Lyapunov function are all subfields of Control theory research. Shouming Zhong has included themes like State and Mathematical optimization in his Artificial neural network study.
The study incorporates disciplines such as Matrix and Lyapunov stability in addition to Exponential stability. Shouming Zhong has researched Stability in several fields, including Numerical stability, Interval, Applied mathematics and Neutral systems. His biological study spans a wide range of topics, including Discrete time and continuous time, Bounded function and Stability criterion.
Shouming Zhong spends much of his time researching Control theory, Artificial neural network, Control theory, Fuzzy logic and Stability. His Fuzzy control system study, which is part of a larger body of work in Control theory, is frequently linked to Data control, bridging the gap between disciplines. His work carried out in the field of Artificial neural network brings together such families of science as Function, State variable, Lyapunov function and Interval.
His Control theory study combines topics in areas such as Discrete time and continuous time, Actuator and Computer simulation. The concepts of his Stability study are interwoven with issues in Quadratic function and Applied mathematics. While the research belongs to areas of Applied mathematics, Shouming Zhong spends his time largely on the problem of Linear matrix inequality, intersecting his research to questions surrounding Stability.
His scientific interests lie mostly in Control theory, Artificial neural network, Fuzzy logic, Applied mathematics and Fuzzy control system. His Control theory study incorporates themes from Sampling and State. His Artificial neural network research includes elements of Basis, Stability, Lyapunov function, Stability and Function.
His Fuzzy logic research incorporates elements of Upper and lower bounds and Event triggered. His Applied mathematics research includes themes of Stability criterion, Linear system, Linear matrix inequality, Exponential stability and Inequality. His research on Fuzzy control system also deals with topics like
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.
Non-fragile memory filtering of T-S fuzzy delayed neural networks based on switched fuzzy sampled-data control
Kaibo Shi;Jun Wang;Shouming Zhong;Yuanyan Tang.
Fuzzy Sets and Systems (2020)
Pinning impulsive synchronization of complex dynamical networks with various time-varying delay sizes
Xin Wang;Xin Wang;Xinzhi Liu;Kun She;Shouming Zhong.
Nonlinear Analysis: Hybrid Systems (2017)
Finite-time filtering for switched linear systems with a mode-dependent average dwell time
Jun Cheng;Hong Zhu;Shouming Zhong;Fengxia Zheng.
Nonlinear Analysis: Hybrid Systems (2015)
Stability criteria for impulsive reaction-diffusion Cohen-Grossberg neural networks with time-varying delays
Jie Pan;Xinzhi Liu;Shouming Zhong.
Mathematical and Computer Modelling (2010)
Improved delay-dependent stability criteria for neural networks with two additive time-varying delay components
Junkang Tian;Shouming Zhong.
Novel delay-dependent robust stability criteria for neutral systems with mixed time-varying delays and nonlinear perturbations
Jun Cheng;Hong Zhu;Shouming Zhong;Guihua Li.
Applied Mathematics and Computation (2013)
Finite-time boundedness of state estimation for neural networks with time-varying delays
Jun Cheng;Shouming Zhong;Qishui Zhong;Hong Zhu.
Finite-time H∞ estimation for discrete-time Markov jump systems with time-varying transition probabilities subject to average dwell time switching
Jun Cheng;Hong Zhu;Shouming Zhong;Qishui Zhong.
Communications in Nonlinear Science and Numerical Simulation (2015)
Robust stability analysis for discrete-time stochastic neural networks systems with time-varying delays
Mengzhuo Luo;Shouming Zhong;Rongjun Wang;Wei Kang.
Applied Mathematics and Computation (2009)
Improved delay-dependent stability criteria for recurrent neural networks with time-varying delays
Xiangbing Zhou;Junkang Tian;Hongjiang Ma;Shouming Zhong.
Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: