What is he best known for?
The fields of study he is best known for:
- Control theory
- Artificial intelligence
- Statistics
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.
His most cited work include:
- Asynchronous l 2 - l ∞ filtering for discrete-time stochastic Markov jump systems with randomly occurred sensor nonlinearities (446 citations)
- Reliable $H_\infty$ Control for Discrete-Time Fuzzy Systems With Infinite-Distributed Delay (161 citations)
- Dissipativity-Based Sampled-Data Fuzzy Control Design and its Application to Truck-Trailer System (107 citations)
What are the main themes of his work throughout his whole career to date?
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.
He most often published in these fields:
- Control theory (70.88%)
- Nonlinear system (20.54%)
- Control theory (18.51%)
What were the highlights of his more recent work (between 2019-2021)?
- Control theory (70.88%)
- Nonlinear system (20.54%)
- Control theory (18.51%)
In recent papers he was focusing on the following fields of study:
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.
Between 2019 and 2021, his most popular works were:
- Energy-to-Peak Filtering of Semi-Markov Jump Systems With Mismatched Modes (8 citations)
- Direct Multivariate Intrinsic Time-Scale Decomposition for Oscillation Monitoring (7 citations)
- $H_\infty$ Output Consensus for Markov Jump Multiagent Systems With Uncertainties (7 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Control theory
- Statistics
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.
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