What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Control theory
Meng Joo Er mostly deals with Fuzzy logic, Artificial intelligence, Control theory, Fuzzy control system and Neuro-fuzzy.
His Fuzzy logic research is multidisciplinary, incorporating perspectives in Mathematical optimization and Backstepping.
His Artificial intelligence study combines topics in areas such as Machine learning, Nonlinear system and Pattern recognition.
His Machine learning research includes elements of Fuzzy classification and Data mining.
The various areas that Meng Joo Er examines in his Fuzzy control system study include Tracking error, Open-loop controller and PID controller.
His work focuses on many connections between Neuro-fuzzy and other disciplines, such as Adaptive neuro fuzzy inference system, that overlap with his field of interest in Defuzzification, Mobile robot and Reinforcement learning.
His most cited work include:
- Face recognition with radial basis function (RBF) neural networks (527 citations)
- Illumination compensation and normalization for robust face recognition using discrete cosine transform in logarithm domain (482 citations)
- Dynamic fuzzy neural networks-a novel approach to function approximation (388 citations)
What are the main themes of his work throughout his whole career to date?
Meng Joo Er focuses on Control theory, Artificial intelligence, Fuzzy logic, Fuzzy control system and Artificial neural network.
His research in Control theory tackles topics such as Control engineering which are related to areas like Robot and Stability.
Meng Joo Er combines subjects such as Machine learning, Computer vision and Pattern recognition with his study of Artificial intelligence.
Meng Joo Er studies Neuro-fuzzy, a branch of Fuzzy logic.
His Fuzzy control system study integrates concerns from other disciplines, such as Tracking error and Exponential stability.
In Artificial neural network, Meng Joo Er works on issues like Pruning, which are connected to Extended Kalman filter.
He most often published in these fields:
- Control theory (52.70%)
- Artificial intelligence (37.84%)
- Fuzzy logic (27.93%)
What were the highlights of his more recent work (between 2014-2021)?
- Control theory (52.70%)
- Artificial intelligence (37.84%)
- Fuzzy logic (27.93%)
In recent papers he was focusing on the following fields of study:
Meng Joo Er spends much of his time researching Control theory, Artificial intelligence, Fuzzy logic, Nonlinear system and Trajectory.
His Artificial intelligence research is multidisciplinary, relying on both Machine learning, Data mining, Computer vision and Pattern recognition.
Meng Joo Er specializes in Machine learning, namely Artificial neural network.
His Fuzzy logic research incorporates themes from Lyapunov function and Interpolation.
His study in the field of Adaptive control is also linked to topics like Class.
In general Fuzzy control system study, his work on Adaptive neuro fuzzy inference system and Neuro-fuzzy often relates to the realm of Pyramid, thereby connecting several areas of interest.
Between 2014 and 2021, his most popular works were:
- A review of clustering techniques and developments (251 citations)
- Adaptive Robust Online Constructive Fuzzy Control of a Complex Surface Vehicle System (138 citations)
- Direct Adaptive Fuzzy Tracking Control of Marine Vehicles With Fully Unknown Parametric Dynamics and Uncertainties (121 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Control theory
His primary scientific interests are in Control theory, Fuzzy logic, Artificial intelligence, Fuzzy control system and Artificial neural network.
His study in Nonlinear system, Vehicle dynamics, Adaptive control, Robustness and Trajectory is carried out as part of his Control theory studies.
His Fuzzy logic research is multidisciplinary, incorporating elements of Control system and Backstepping.
The Artificial intelligence study combines topics in areas such as Machine learning and Computer vision.
As a part of the same scientific study, Meng Joo Er usually deals with the Machine learning, concentrating on Data mining and frequently concerns with Fuzzy clustering, Unsupervised learning and Mode.
His work carried out in the field of Fuzzy control system brings together such families of science as Tracking error, Proportional derivative and Lyapunov function.
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