What is he best known for?
The fields of study he is best known for:
- Mathematical analysis
- Control theory
- Artificial neural network
Tianping Chen spends much of his time researching Control theory, Artificial neural network, Synchronization, Exponential stability and Synchronization of chaos.
In Control theory, Tianping Chen works on issues like Complex network, which are connected to Control theory.
The various areas that he examines in his Artificial neural network study include Stability, Mathematical optimization, Applied mathematics and Nonlinear system.
Tianping Chen combines subjects such as Hopfield network and Algorithm with his study of Stability.
His work on Synchronization networks as part of general Synchronization study is frequently connected to Differential equation, Chaotic, Cellular neural network and Measure, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His Exponential stability study incorporates themes from Equilibrium point and Linear matrix inequality.
His most cited work include:
- Pinning Complex Networks by a Single Controller (824 citations)
- New approach to synchronization analysis of linearly coupled ordinary differential systems (465 citations)
- Universal approximation to nonlinear operators by neural networks with arbitrary activation functions and its application to dynamical systems (345 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Artificial neural network, Control theory, Synchronization, Dynamical systems theory and Topology.
His Artificial neural network research incorporates elements of Equilibrium point, Stability, Exponential stability, Mathematical optimization and Applied mathematics.
His research investigates the link between Exponential stability and topics such as Mathematical analysis that cross with problems in Continuous function.
The Control theory study combines topics in areas such as Chaotic and Differential equation.
His Dynamical systems theory research incorporates themes from Dynamical system and Stability theory.
His study in Topology is interdisciplinary in nature, drawing from both Multi-agent system, Graph and Graph theory.
He most often published in these fields:
- Artificial neural network (44.72%)
- Control theory (44.72%)
- Synchronization (25.47%)
What were the highlights of his more recent work (between 2014-2021)?
- Control theory (44.72%)
- Topology (21.74%)
- Synchronization (25.47%)
In recent papers he was focusing on the following fields of study:
Tianping Chen mostly deals with Control theory, Topology, Synchronization, Multi-agent system and Artificial neural network.
His research in the fields of Dynamical systems theory, Control theory and Adaptive algorithm overlaps with other disciplines such as Synchronization and Computer simulation.
Tianping Chen usually deals with Topology and limits it to topics linked to Event triggered and Scheduling.
His Synchronization research overlaps with other disciplines such as Complex network, Adaptive system and Component.
His Multi-agent system study which covers Spanning tree that intersects with Consensus, Laplace operator, Rate of convergence, Digraph and Laplacian matrix.
Tianping Chen interconnects Equilibrium point, Nonlinear system and State in the investigation of issues within Artificial neural network.
Between 2014 and 2021, his most popular works were:
- Synchronization of Complex Networks via Aperiodically Intermittent Pinning Control (172 citations)
- Synchronization of Nonlinear Coupled Networks via Aperiodically Intermittent Pinning Control (158 citations)
- Synchronization of Linearly Coupled Networks With Delays via Aperiodically Intermittent Pinning Control (133 citations)
In his most recent research, the most cited papers focused on:
- Mathematical analysis
- Control theory
- Topology
The scientist’s investigation covers issues in Control theory, Synchronization, Complex network, Nonlinear system and Control theory.
In general Control theory, his work in Adaptive algorithm is often linked to Synchronization linking many areas of study.
Among his Synchronization studies, there is a synthesis of other scientific areas such as Artificial neural network, Node, Adaptive system and Term.
His research on Artificial neural network frequently links to adjacent areas such as Flow.
As part of one scientific family, he deals mainly with the area of Complex network, narrowing it down to issues related to the Correctness, and often Trajectory and Ordinary differential equation.
His research integrates issues of Numerical stability, Mathematical analysis and Positive systems in his study of Nonlinear system.
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