Control theory, Linear matrix inequality, Artificial neural network, Control theory and Lyapunov function are his primary areas of study. His research ties Filter and Control theory together. His Linear matrix inequality study integrates concerns from other disciplines, such as Passivity, Time delays, Delay dependent and Stability.
His Artificial neural network study combines topics from a wide range of disciplines, such as Lyapunov functional, State, Observer and Synchronization. Hongye Su studied Control theory and Sampling that intersect with Multiplicative function. Hidden Markov model, Markov chain and Stochastic stability is closely connected to Markov process in his research, which is encompassed under the umbrella topic of Lyapunov function.
Hongye Su spends much of his time researching Control theory, Nonlinear system, Control theory, Linear matrix inequality and Mathematical optimization. His research integrates issues of State and Bounded function in his study of Control theory. Nonlinear system is closely attributed to Estimation theory in his study.
His Control theory research includes elements of Control and Lyapunov function. His study connects Markov process and Lyapunov function. His biological study spans a wide range of topics, including Filter, Artificial neural network, Exponential stability, Stability and Singular systems.
Hongye Su focuses on Control theory, Nonlinear system, Control theory, Bounded function and Control. His Control theory research incorporates themes from Wireless power transfer, Multi-agent system and Voltage regulation. His Nonlinear system study incorporates themes from Multivariate statistics and Stability.
The concepts of his Control theory study are interwoven with issues in Exponential stability, Boundary value problem, Reliability and Conjunctive normal form. His work deals with themes such as Event, Estimation theory, State, Petri net and Computer simulation, which intersect with Bounded function. His Control study combines topics in areas such as Turbulence, Minimum-variance unbiased estimator and Benchmark.
Hongye Su mainly investigates Control theory, Control theory, Markov process, Nonlinear system and Decomposition. He does research in Control theory, focusing on Adaptive control specifically. He works mostly in the field of Control theory, limiting it down to topics relating to Bounded function and, in certain cases, Event, Petri net and Conjunctive normal form.
His Markov process research incorporates themes from Lyapunov function, Impulse response, Interlacing, Upper and lower bounds and Polynomial. His research in Lyapunov function intersects with topics in Filter, Stochastic process, Linear matrix inequality, Filtering problem and Energy. The concepts of his Nonlinear system study are interwoven with issues in Induced oscillations, In process control, Mode and Noise measurement.
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.
Asynchronous l 2 - l ∞ filtering for discrete-time stochastic Markov jump systems with randomly occurred sensor nonlinearities
Zheng-Guang Wu;Peng Shi;Hongye Su;Jian Chu.
Automatica (2014)
Reliable $H_\infty$ Control for Discrete-Time Fuzzy Systems With Infinite-Distributed Delay
Zheng-Guang Wu;Peng Shi;Hongye Su;Jian Chu.
IEEE Transactions on Fuzzy Systems (2009)
Exponential $\mathcal {H}_{\infty }$ Filtering for Discrete-Time Switched Neural Networks With Random Delays
Kalidass Mathiyalagan;Hongye Su;Peng Shi;Rathinasamy Sakthivel.
IEEE Transactions on Systems, Man, and Cybernetics (2015)
Dissipativity-Based Sampled-Data Fuzzy Control Design and its Application to Truck-Trailer System
Zheng-Guang Wu;Peng Shi;Hongye Su;Renquan Lu.
IEEE Transactions on Fuzzy Systems (2015)
Adaptive Synchronization for Neutral-Type Neural Networks with Stochastic Perturbation and Markovian Switching Parameters
Wuneng Zhou;Qingyu Zhu;Peng Shi;Hongye Su.
IEEE Transactions on Systems, Man, and Cybernetics (2014)
l2-l∞ filter design for discrete-time singular Markovian jump systems with time-varying delays
Zheng-Guang Wu;Peng Shi;Hongye Su;Jian Chu.
Information Sciences (2011)
Robust dissipativity analysis of neural networks with time-varying delay and randomly occurring uncertainties
Zheng-Guang Wu;Zheng-Guang Wu;Ju H. Park;Hongye Su;Jian Chu.
Nonlinear Dynamics (2012)
Improved Delay-Dependent Stability Condition of Discrete Recurrent Neural Networks With Time-Varying Delays
Zhengguang Wu;Hongye Su;Jian Chu;Wuneng Zhou.
IEEE Transactions on Neural Networks (2010)
Optimal Estimation in UDP-Like Networked Control Systems With Intermittent Inputs: Stability Analysis and Suboptimal Filter Design
Hong Lin;Hongye Su;Zhan Shu;Zheng-Guang Wu.
IEEE Transactions on Automatic Control (2016)
State estimation for discrete Markovian jumping neural networks with time delay
Zhengguang Wu;Hongye Su;Jian Chu.
Neurocomputing (2010)
Journal of Industrial and Management Optimization
(Impact Factor: 1.411)
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