2022 - Research.com Rising Star of Science Award
His primary areas of study are Control theory, Nonlinear system, Upper and lower bounds, Covariance and Filtering problem. His Control theory investigation overlaps with other areas such as Bernoulli distribution and Conditional probability. The various areas that he examines in his Nonlinear system study include Data mining and Quantization.
His research in Upper and lower bounds intersects with topics in Mathematical optimization and Linearization. His work in Filtering problem addresses subjects such as Applied mathematics, which are connected to disciplines such as Recursive filter. His Filter design course of study focuses on Probabilistic logic and Complex network.
Jun Hu mainly focuses on Control theory, Nonlinear system, Upper and lower bounds, Bernoulli's principle and Covariance. His work on Sliding mode control, Control theory and Filtering problem as part of general Control theory research is frequently linked to Stochastic process, bridging the gap between disciplines. His Sliding mode control study incorporates themes from Reachability and System dynamics.
As a part of the same scientific study, he usually deals with the Control theory, concentrating on Discrete time and continuous time and frequently concerns with State. His research integrates issues of Probabilistic logic and Quantization in his study of Nonlinear system. His Upper and lower bounds research is multidisciplinary, incorporating elements of Function, Lyapunov function, Applied mathematics and Complex network.
His primary areas of investigation include Control theory, Nonlinear system, Algorithm, Bernoulli's principle and Sliding mode control. Control theory is closely attributed to Bounded function in his work. He has researched Nonlinear system in several fields, including Stochastic differential equation, Applied mathematics, Event triggered and Distributed filtering.
His Algorithm study combines topics from a wide range of disciplines, such as Kalman filter, Upper and lower bounds and Outlier. His work is dedicated to discovering how Upper and lower bounds, Complex network are connected with Covariance matrix and other disciplines. His study on Sliding mode control also encompasses disciplines like
His primary areas of study are Control theory, Nonlinear system, Algorithm, Upper and lower bounds and Bernoulli distribution. As part of his studies on Control theory, Jun Hu frequently links adjacent subjects like Bounded function. The Nonlinear system study combines topics in areas such as Finite time and Filter design.
Jun Hu conducted interdisciplinary study in his works that combined Upper and lower bounds and Covariance. His Sliding mode control research is multidisciplinary, relying on both Dynamical system, Linear matrix inequality, Time delays and Singular systems. His Complex network research incorporates elements of Covariance matrix and Applied mathematics.
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Quantised recursive filtering for a class of nonlinear systems with multiplicative noises and missing measurements
Jun Hu;Zidong Wang;Bo Shen;Huijun Gao.
International Journal of Control (2013)
A variance-constrained approach to recursive state estimation for time-varying complex networks with missing measurements
Jun Hu;Zidong Wang;Steven Liu;Huijun Gao.
Robust Sliding Mode Control for Discrete Stochastic Systems With Mixed Time Delays, Randomly Occurring Uncertainties, and Randomly Occurring Nonlinearities
Jun Hu;Zidong Wang;Huijun Gao;L. K. Stergioulas.
IEEE Transactions on Industrial Electronics (2012)
Extended Kalman filtering with stochastic nonlinearities and multiple missing measurements
Jun Hu;Zidong Wang;Huijun Gao;Lampros K. Stergioulas.
Fuzzy-Logic-Based Control, Filtering, and Fault Detection for Networked Systems: A Survey
Yuqiang Luo;Zidong Wang;Guoliang Wei;Bo Shen.
Mathematical Problems in Engineering (2015)
Gain-Constrained Recursive Filtering With Stochastic Nonlinearities and Probabilistic Sensor Delays
Jun Hu;Zidong Wang;Bo Shen;Huijun Gao.
IEEE Transactions on Signal Processing (2013)
State estimation for a class of discrete nonlinear systems with randomly occurring uncertainties and distributed sensor delays
Jun Hu;Dongyan Chen;Junhua Du.
International Journal of General Systems (2014)
Recursive filtering with random parameter matrices, multiple fading measurements and correlated noises
Jun Hu;Jun Hu;Zidong Wang;Zidong Wang;Huijun Gao;Huijun Gao.
Estimation, filtering and fusion for networked systems with network-induced phenomena
Jun Hu;Zidong Wang;Dongyan Chen;Fuad E. Alsaadi.
Information Fusion (2016)
Event-based filtering for time-varying nonlinear systems subject to multiple missing measurements with uncertain missing probabilities
Jun Hu;Zidong Wang;Zidong Wang;Fuad E. Alsaadi;Tasawar Hayat.
Information Fusion (2017)
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