What is he best known for?
The fields of study he is best known for:
- Control theory
- Artificial intelligence
- Mathematical analysis
The scientist’s investigation covers issues in Control theory, Artificial neural network, Linear matrix inequality, Control theory and Exponential stability.
His Control theory study frequently involves adjacent topics like Stability criterion.
His Artificial neural network research includes elements of Stability, Symmetric matrix, Interval and Synchronization.
His studies deal with areas such as Norm, Lyapunov stability and Convex optimization as well as Linear matrix inequality.
His biological study deals with issues like Control, which deal with fields such as Markov jump.
His biological study spans a wide range of topics, including Zero and State.
His most cited work include:
- Extended Dissipative State Estimation for Markov Jump Neural Networks With Unreliable Links (336 citations)
- Stability of time-delay systems via Wirtinger-based double integral inequality (259 citations)
- Reliable mixed passive and ℋ∞ filtering for semi‐Markov jump systems with randomly occurring uncertainties and sensor failures (246 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Control theory, Control theory, Nonlinear system, Artificial neural network and Exponential stability.
His study in Control theory is interdisciplinary in nature, drawing from both Interval and Fuzzy logic.
The Nonlinear system study combines topics in areas such as Function, Bounded function and Filter.
The concepts of his Artificial neural network study are interwoven with issues in Stability, State and Synchronization.
His Exponential stability research focuses on Stability criterion and how it connects with Circle criterion.
He studied Linear matrix inequality and Convex optimization that intersect with Mathematical optimization.
He most often published in these fields:
- Control theory (78.16%)
- Control theory (21.70%)
- Nonlinear system (21.56%)
What were the highlights of his more recent work (between 2019-2021)?
- Control theory (78.16%)
- Nonlinear system (21.56%)
- Control theory (21.70%)
In recent papers he was focusing on the following fields of study:
Ju H. Park focuses on Control theory, Nonlinear system, Control theory, Fuzzy logic and Artificial neural network.
His study ties his expertise on Bounded function together with the subject of Control theory.
His studies in Nonlinear system integrate themes in fields like Function, Multi-agent system and Fault tolerance.
In Control theory, he works on issues like Exponential stability, which are connected to Applied mathematics.
The various areas that Ju H. Park examines in his Fuzzy logic study include Observer, Control system, Convex combination and Asynchronous communication.
His Artificial neural network study combines topics from a wide range of disciplines, such as Memristor, Reaction–diffusion system and Synchronization.
Between 2019 and 2021, his most popular works were:
- Hidden Markov Model-Based Nonfragile State Estimation of Switched Neural Network With Probabilistic Quantized Outputs (92 citations)
- Quantized Nonstationary Filtering of Networked Markov Switching RSNSs: A Multiple Hierarchical Structure Strategy (74 citations)
- Reliable Event-Triggered Asynchronous Extended Passive Control for Semi-Markov Jump Fuzzy Systems and Its Application (55 citations)
In his most recent research, the most cited papers focused on:
- Control theory
- Artificial intelligence
- Mathematical analysis
Ju H. Park mainly focuses on Control theory, Control theory, Fuzzy logic, Nonlinear system and Fuzzy control system.
Ju H. Park works on Control theory which deals in particular with Actuator.
His work carried out in the field of Control theory brings together such families of science as Upper and lower bounds, State, Interval and Stability theory.
His research integrates issues of Observer, Convex combination, Discrete time and continuous time and Applied mathematics in his study of Fuzzy logic.
His Nonlinear system study incorporates themes from Norm, Bounded function and Filter.
His Artificial neural network research is multidisciplinary, relying on both Stability, Memristor and Synchronization.
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