What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Control theory
- Artificial neural network
His primary scientific interests are in Control theory, Artificial neural network, Exponential stability, Linear matrix inequality and Nonlinear system.
Shumin Fei integrates Control theory and Convex combination in his studies.
His Artificial neural network research is multidisciplinary, incorporating elements of MATLAB, Adaptive control and Filter.
His work carried out in the field of Exponential stability brings together such families of science as Recurrent neural network, Fixed-point theorem, Applied mathematics, Monotonic function and Lipschitz continuity.
His Linear matrix inequality research includes elements of Stability criterion, Lyapunov stability, Filter design, Stability theory and Interval.
His Nonlinear system study which covers Control theory that intersects with Tracking, Nonholonomic system, Trajectory, Torque and Feed forward.
His most cited work include:
- Combined Convex Technique on Delay-Dependent Stability for Delayed Neural Networks (88 citations)
- Advances in Neural Networks – ISNN 2007 (84 citations)
- Synchronization control of recurrent neural networks with distributed delays (75 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Control theory, Nonlinear system, Control theory, Artificial neural network and Exponential stability.
Control theory is a component of his Lyapunov function, Linear matrix inequality, Adaptive control, Control system and Stability studies.
In the subject of general Nonlinear system, his work in Nonlinear control, Tracking error and Backstepping is often linked to Integrator, thereby combining diverse domains of study.
His study in Nonlinear control is interdisciplinary in nature, drawing from both Mathematical optimization and Output feedback.
His Radial basis function study in the realm of Artificial neural network connects with subjects such as Convex combination.
His Exponential stability research integrates issues from Robust control and Applied mathematics.
He most often published in these fields:
- Control theory (74.15%)
- Nonlinear system (26.89%)
- Control theory (20.10%)
What were the highlights of his more recent work (between 2017-2021)?
- Control theory (74.15%)
- Control theory (20.10%)
- Artificial intelligence (14.88%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Control theory, Control theory, Artificial intelligence, Nonlinear system and Computer vision.
His Control theory research incorporates themes from Artificial neural network and Control.
His Control theory research is multidisciplinary, relying on both Observer, Master/slave, Chaotic and Actuator.
His Artificial intelligence research is multidisciplinary, incorporating perspectives in Simultaneous localization and mapping and Pattern recognition.
His work on Backstepping and Robust control as part of general Nonlinear system study is frequently connected to Dissipative system and Constraint, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His Exponential stability study combines topics from a wide range of disciplines, such as Discrete time and continuous time, Applied mathematics, Lyapunov function and Filter.
Between 2017 and 2021, his most popular works were:
- Hybrid-driven-based H∞ filter design for neural networks subject to deception attacks (53 citations)
- Regional Stabilization for Discrete Time-Delay Systems With Actuator Saturations via A Delay-Dependent Polytopic Approach (34 citations)
- Hybrid-driven H∞ filter design for T–S fuzzy systems with quantization (33 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Control theory
- Computer vision
Shumin Fei mainly focuses on Control theory, Linear matrix inequality, Event triggered, Control theory and Exponential stability.
Shumin Fei regularly ties together related areas like Artificial neural network in his Control theory studies.
His Artificial neural network study integrates concerns from other disciplines, such as Derivative and Lyapunov function.
In his research on the topic of Linear matrix inequality, Fuzzy control system and Filter model is strongly related with Filter design.
In his study, Tracking error, Stability criterion, Frequency domain and Describing function is inextricably linked to Actuator, which falls within the broad field of Control theory.
His Exponential stability research focuses on Applied mathematics and how it connects with Piecewise, Positive-definite matrix, Monotonic function and Piecewise linear function.
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