2022 - Research.com Rising Star of Science Award
His primary scientific interests are in Control theory, Artificial neural network, Memristor, Synchronization and Recurrent neural network. His Control theory and Exponential stability, Nonlinear system, Sliding mode control, Fuzzy control system and Control system investigations all form part of his Control theory research activities. His Artificial neural network research is multidisciplinary, incorporating elements of Synapse and Fuzzy logic.
Shiping Wen combines subjects such as Compensation, Lyapunov function, Convolutional neural network and CMOS with his study of Fuzzy logic. His work carried out in the field of Memristor brings together such families of science as Differential inclusion, Class and Adaptive control. His Recurrent neural network study integrates concerns from other disciplines, such as Exponential passivity, Passivity, Content-addressable memory and Differential equation.
Shiping Wen spends much of his time researching Artificial neural network, Control theory, Memristor, Artificial intelligence and Synchronization. His Artificial neural network study incorporates themes from Event, Quaternion, Exponential function, Applied mathematics and Electronic engineering. His is doing research in Nonlinear system, Control theory, Lyapunov function, Exponential stability and Linear matrix inequality, both of which are found in Control theory.
His Nonlinear system research incorporates themes from Control system and Passivity. He interconnects Recurrent neural network, Content-addressable memory, Convolutional neural network and Fuzzy logic in the investigation of issues within Memristor. Shiping Wen has researched Artificial intelligence in several fields, including Machine learning, Synapse and Pattern recognition.
His scientific interests lie mostly in Artificial neural network, Control theory, Memristor, Lyapunov function and Control theory. His Artificial neural network study combines topics from a wide range of disciplines, such as Equilibrium point, Exponential stability, Mathematical optimization and Multistability. His study looks at the intersection of Exponential stability and topics like State space with Stability theory and Cellular neural network.
His work on Disturbance and Passivity as part of general Control theory study is frequently linked to Synchronization, Event based and Event, bridging the gap between disciplines. His studies deal with areas such as Convolutional neural network and Computer engineering as well as Memristor. His work on Sliding mode control as part of general Control theory research is often related to Leakage, thus linking different fields of science.
His main research concerns Artificial neural network, Control theory, Memristor, Computer engineering and Synchronization. Artificial neural network is closely attributed to Quaternion in his work. Control theory and Lyapunov function are the core of his Control theory study.
The study incorporates disciplines such as Finite time, Norm, Uniform boundedness and Nonlinear system in addition to Control theory. Shiping Wen works mostly in the field of Memristor, limiting it down to topics relating to Convolutional neural network and, in certain cases, Edge computing and Quantization. His Computer engineering research includes themes of Encoding, Reduction, Sigmoid function, Activation function and Test set.
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.
Synchronization control of a class of memristor-based recurrent neural networks
Ailong Wu;Shiping Wen;Zhigang Zeng.
Information Sciences (2012)
Event-Triggering Load Frequency Control for Multiarea Power Systems With Communication Delays
Shiping Wen;Xinghuo Yu;Zhigang Zeng;Jinjian Wang.
IEEE Transactions on Industrial Electronics (2016)
Exponential Adaptive Lag Synchronization of Memristive Neural Networks via Fuzzy Method and Applications in Pseudorandom Number Generators
Shiping Wen;Zhigang Zeng;Tingwen Huang;Yide Zhang.
IEEE Transactions on Fuzzy Systems (2014)
Lag Synchronization of Switched Neural Networks via Neural Activation Function and Applications in Image Encryption
Shiping Wen;Zhigang Zeng;Tingwen Huang;Qinggang Meng.
IEEE Transactions on Neural Networks (2015)
Fuzzy Control for Uncertain Vehicle Active Suspension Systems via Dynamic Sliding-Mode Approach
Shiping Wen;Michael Z. Q. Chen;Zhigang Zeng;Xinghuo Yu.
systems man and cybernetics (2017)
A short-term power load forecasting model based on the generalized regression neural network with decreasing step fruit fly optimization algorithm
Rui Hu;Shiping Wen;Zhigang Zeng;Tingwen Huang.
Global exponential synchronization of memristor-based recurrent neural networks with time-varying delays
Shiping Wen;Gang Bao;Zhigang Zeng;Yiran Chen.
Neural Networks (2013)
Exponential stability analysis of memristor-based recurrent neural networks with time-varying delays
Shiping Wen;Zhigang Zeng;Tingwen Huang.
Circuit design and exponential stabilization of memristive neural networks
Shiping Wen;Tingwen Huang;Zhigang Zeng;Yiran Chen.
Neural Networks (2015)
Synchronization of Switched Neural Networks With Communication Delays via the Event-Triggered Control
Shiping Wen;Zhigang Zeng;Michael Z. Q. Chen;Tingwen Huang.
IEEE Transactions on Neural Networks (2017)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: