H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Electronics and Electrical Engineering H-index 46 Citations 5,636 146 World Ranking 1419 National Ranking 158

Research.com Recognitions

Awards & Achievements

2015 - SPIE Fellow

Overview

What is he best known for?

The fields of study he is best known for:

  • Control theory
  • Mathematical analysis
  • Artificial neural network

Zhanshan Wang mainly investigates Control theory, Artificial neural network, Exponential stability, Linear matrix inequality and Recurrent neural network. His Control theory study combines topics in areas such as Upper and lower bounds and Interval. The concepts of his Artificial neural network study are interwoven with issues in Stability, Discrete time and continuous time, Control theory, Mathematical optimization and Stability conditions.

Zhanshan Wang works mostly in the field of Exponential stability, limiting it down to topics relating to Applied mathematics and, in certain cases, Structure and Cellular neural network. In his research, Uniqueness is intimately related to Equilibrium point, which falls under the overarching field of Linear matrix inequality. His Recurrent neural network research is multidisciplinary, relying on both Content-addressable memory, Lyapunov function and Multistability.

His most cited work include:

  • A Comprehensive Review of Stability Analysis of Continuous-Time Recurrent Neural Networks (378 citations)
  • Novel Weighting-Delay-Based Stability Criteria for Recurrent Neural Networks With Time-Varying Delay (336 citations)
  • Global Asymptotic Stability of Recurrent Neural Networks With Multiple Time-Varying Delays (311 citations)

What are the main themes of his work throughout his whole career to date?

His primary areas of study are Control theory, Artificial neural network, Exponential stability, Linear matrix inequality and Stability. His work in Control theory tackles topics such as Interval which are related to areas like Fuzzy logic. His Artificial neural network research incorporates elements of State, Discrete time and continuous time, Lyapunov function, Mathematical optimization and Applied mathematics.

His Exponential stability research includes elements of Equilibrium point, Recurrent neural network, Cellular neural network and Uniqueness. He combines topics linked to Lyapunov stability with his work on Linear matrix inequality. His Stability research focuses on Stability criterion and how it connects with Multiple integral.

He most often published in these fields:

  • Control theory (72.69%)
  • Artificial neural network (48.46%)
  • Exponential stability (22.03%)

What were the highlights of his more recent work (between 2019-2021)?

  • Control theory (72.69%)
  • Artificial neural network (48.46%)
  • Control theory (13.22%)

In recent papers he was focusing on the following fields of study:

His scientific interests lie mostly in Control theory, Artificial neural network, Control theory, Applied mathematics and Fuzzy control system. Particularly relevant to Stability is his body of work in Control theory. His study looks at the intersection of Artificial neural network and topics like State with Activation function.

His studies in Control theory integrate themes in fields like Trajectory and Synchronization. His research integrates issues of Markovian jump, Derivative and Differential equation in his study of Applied mathematics. His Fuzzy control system research also works with subjects such as

  • Integral sliding mode which is related to area like Error function and Linear matrix inequality,
  • Function and related Sliding mode control and Linear system,
  • Variable which is related to area like Markov chain and State variable.

Between 2019 and 2021, his most popular works were:

  • Barrier Lyapunov Function-Based Adaptive Fuzzy FTC for Switched Systems and Its Applications to Resistance–Inductance–Capacitance Circuit System (54 citations)
  • Event-triggered synchronization of discrete-time neural networks: A switching approach. (42 citations)
  • Extended Dissipativity Analysis for Markovian Jump Neural Networks via Double-Integral-Based Delay-Product-Type Lyapunov Functional. (15 citations)

In his most recent research, the most cited papers focused on:

  • Control theory
  • Mathematical analysis
  • Electrical engineering

His primary scientific interests are in Control theory, Artificial neural network, Applied mathematics, Control theory and Fuzzy logic. The study incorporates disciplines such as Initial value problem, Interval and Multiple integral in addition to Control theory. His studies deal with areas such as Control system and Upper and lower bounds as well as Interval.

In his study, Polynomial and Stability criterion is strongly linked to Stability, which falls under the umbrella field of Multiple integral. Zhanshan Wang interconnects State and Inequality in the investigation of issues within Applied mathematics. Within one scientific family, Zhanshan Wang focuses on topics pertaining to Nonlinear system under Fuzzy logic, and may sometimes address concerns connected to Instability and Bounded function.

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.

Top Publications

A Comprehensive Review of Stability Analysis of Continuous-Time Recurrent Neural Networks

Huaguang Zhang;Zhanshan Wang;Derong Liu.
IEEE Transactions on Neural Networks (2014)

452 Citations

Novel Weighting-Delay-Based Stability Criteria for Recurrent Neural Networks With Time-Varying Delay

Huaguang Zhang;Zhenwei Liu;Guang-Bin Huang;Zhanshan Wang.
IEEE Transactions on Neural Networks (2010)

373 Citations

Global Asymptotic Stability of Recurrent Neural Networks With Multiple Time-Varying Delays

Huaguang Zhang;Zhanshan Wang;Derong Liu.
IEEE Transactions on Neural Networks (2008)

338 Citations

Global Asymptotic Stability of Reaction–Diffusion Cohen–Grossberg Neural Networks With Continuously Distributed Delays

Zhanshan Wang;Huaguang Zhang.
IEEE Transactions on Neural Networks (2010)

182 Citations

Adaptive Fault-Tolerant Tracking Control for MIMO Discrete-Time Systems via Reinforcement Learning Algorithm With Less Learning Parameters

Lei Liu;Zhanshan Wang;Huaguang Zhang.
IEEE Transactions on Automation Science and Engineering (2017)

176 Citations

Robust Stability Analysis for Interval Cohen–Grossberg Neural Networks With Unknown Time-Varying Delays

Huaguang Zhang;Zhanshan Wang;Derong Liu.
IEEE Transactions on Neural Networks (2008)

167 Citations

LMI-Based Approach for Global Asymptotic Stability Analysis of Recurrent Neural Networks with Various Delays and Structures

Zhanshan Wang;Huaguang Zhang;Bin Jiang.
IEEE Transactions on Neural Networks (2011)

166 Citations

Robust Exponential Stability of Recurrent Neural Networks With Multiple Time-Varying Delays

Huaguang Zhang;Zhanshan Wang;Derong Liu.
IEEE Transactions on Circuits and Systems Ii-express Briefs (2007)

151 Citations

Global Asymptotic Stability and Robust Stability of a Class of Cohen–Grossberg Neural Networks With Mixed Delays

Huaguang Zhang;Zhanshan Wang;Derong Liu.
IEEE Transactions on Circuits and Systems (2009)

147 Citations

Data-Core-Based Fuzzy Min–Max Neural Network for Pattern Classification

Huaguang Zhang;Jinhai Liu;Dazhong Ma;Zhanshan Wang.
IEEE Transactions on Neural Networks (2011)

147 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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