His primary areas of investigation include Control theory, Nonlinear system, Adaptive control, Backstepping and Artificial neural network. Control theory is closely attributed to Fuzzy logic in his work. His Nonlinear system research is multidisciplinary, relying on both Multi-agent system, Bounded function and Cryptography.
As part of one scientific family, C. L. Philip Chen deals mainly with the area of Adaptive control, narrowing it down to issues related to the State, and often Trajectory, Torque, Type, Stability and Constraint. His studies deal with areas such as Observer, Tracking error and Adaptive neuro fuzzy inference system as well as Backstepping. C. L. Philip Chen combines subjects such as Incremental learning, MIMO and Inference with his study of Artificial neural network.
His primary scientific interests are in Control theory, Artificial intelligence, Nonlinear system, Pattern recognition and Artificial neural network. Control theory is frequently linked to Fuzzy logic in his study. The study incorporates disciplines such as Machine learning and Computer vision in addition to Artificial intelligence.
His research in Nonlinear system intersects with topics in Multi-agent system, Bounded function, Actuator and Adaptive system. His Pattern recognition research includes themes of Pixel and Feature. His Artificial neural network study which covers Robustness that intersects with Outlier.
C. L. Philip Chen mostly deals with Control theory, Nonlinear system, Artificial intelligence, Artificial neural network and Control theory. His work on Control theory is being expanded to include thematically relevant topics such as Fuzzy logic. His study on Nonlinear system also encompasses disciplines like
The Artificial intelligence study combines topics in areas such as Machine learning and Pattern recognition. His Artificial neural network research is multidisciplinary, incorporating elements of Control system, Algorithm, Estimator and Robot. Outlier is closely connected to Robustness in his research, which is encompassed under the umbrella topic of Control theory.
C. L. Philip Chen spends much of his time researching Control theory, Nonlinear system, Artificial neural network, Control theory and Artificial intelligence. His Control theory and Lyapunov function, Backstepping, Adaptive control, Stability and State observer investigations all form part of his Control theory research activities. His Nonlinear system study integrates concerns from other disciplines, such as Bounded function, Actuator, Adaptive system and Fuzzy control system.
His Artificial neural network study incorporates themes from Feature, Multi-agent system, Trajectory optimization, Algorithm and Robustness. His studies deal with areas such as Reduced order, Markov process, Trajectory and Robot manipulator as well as Control theory. The study incorporates disciplines such as Invariant, Computer vision and Pattern recognition in addition to Artificial intelligence.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Data-intensive applications, challenges, techniques and technologies: A survey on Big Data
C. L. Philip Chen;Chun-Yang Zhang.
Information Sciences (2014)
A new 1D chaotic system for image encryption
Yicong Zhou;Long Bao;C.L. Philip Chen.
Signal Processing (2014)
A survey of communication/networking in Smart Grids
Jingcheng Gao;Yang Xiao;Jing Liu;Wei Liang.
Future Generation Computer Systems (2012)
Broad Learning System: An Effective and Efficient Incremental Learning System Without the Need for Deep Architecture
C. L. Philip Chen;Zhulin Liu.
IEEE Transactions on Neural Networks (2018)
Cyber Security and Privacy Issues in Smart Grids
Jing Liu;Yang Xiao;Shuhui Li;Wei Liang.
IEEE Communications Surveys and Tutorials (2012)
Adaptive Consensus Control for a Class of Nonlinear Multiagent Time-Delay Systems Using Neural Networks
C. L. Philip Chen;Guo-Xing Wen;Yan-Jun Liu;Fei-Yue Wang.
IEEE Transactions on Neural Networks (2014)
2D Sine Logistic modulation map for image encryption
Zhongyun Hua;Yicong Zhou;Chi-Man Pun;C.L. Philip Chen.
Information Sciences (2015)
A Local Contrast Method for Small Infrared Target Detection
C. L. Philip Chen;Hong Li;Yantao Wei;Tian Xia.
IEEE Transactions on Geoscience and Remote Sensing (2014)
Observer-Based Adaptive Backstepping Consensus Tracking Control for High-Order Nonlinear Semi-Strict-Feedback Multiagent Systems
C. L. Philip Chen;Guo-Xing Wen;Yan-Jun Liu;Zhi Liu.
IEEE Transactions on Systems, Man, and Cybernetics (2016)
Fuzzy Neural Network-Based Adaptive Control for a Class of Uncertain Nonlinear Stochastic Systems
C. L. Philip Chen;Yan-Jun Liu;Guo-Xing Wen.
IEEE Transactions on Systems, Man, and Cybernetics (2014)
Profile was last updated on December 6th, 2021.
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