What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Quantum mechanics
- Computer network
His scientific interests lie mostly in Control theory, Mathematical optimization, Memristor, Economic dispatch and Synchronization.
His research in Control theory intersects with topics in Chaotic ant swarm and Identification.
Many of his studies on Mathematical optimization involve topics that are commonly interrelated, such as Chaotic.
His Memristor research is multidisciplinary, incorporating perspectives in Artificial neural network and Lyapunov functional.
His Artificial neural network study combines topics from a wide range of disciplines, such as Differential inclusion, Type and Synchronization.
Lixiang Li has included themes like Evolutionary algorithm, Chaotic particle swarm optimization and Fuzzy control system in his Economic dispatch study.
His most cited work include:
- CHAOTIC PARTICLE SWARM OPTIMIZATION FOR ECONOMIC DISPATCH CONSIDERING THE GENERATOR CONSTRAINTS (228 citations)
- A multi-objective chaotic particle swarm optimization for environmental/economic dispatch (159 citations)
- Parameters identification of chaotic systems via chaotic ant swarm (116 citations)
What are the main themes of his work throughout his whole career to date?
Lixiang Li mainly focuses on Control theory, Synchronization, Artificial neural network, Chaotic and Memristor.
He works mostly in the field of Control theory, limiting it down to topics relating to Synchronization and, in certain cases, Lyapunov stability, as a part of the same area of interest.
Lixiang Li combines subjects such as Stability, Lag and Settling time with his study of Artificial neural network.
As part of the same scientific family, Lixiang Li usually focuses on Chaotic, concentrating on Mathematical optimization and intersecting with Economic dispatch.
Lixiang Li works mostly in the field of Memristor, limiting it down to topics relating to Differential inclusion and, in certain cases, Computational intelligence.
His work in Optimization problem covers topics such as Swarm intelligence which are related to areas like Artificial intelligence.
He most often published in these fields:
- Control theory (25.20%)
- Synchronization (17.32%)
- Artificial neural network (16.54%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial neural network (16.54%)
- Control theory (25.20%)
- Synchronization (17.32%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Artificial neural network, Control theory, Synchronization, Memristor and Encryption.
His work deals with themes such as Leakage, Lag and Synchronization, which intersect with Artificial neural network.
As a member of one scientific family, he mostly works in the field of Synchronization, focusing on Control theory and, on occasion, Linear matrix inequality.
His research investigates the link between Control theory and topics such as Correctness that cross with problems in Verifiable secret sharing.
He has researched Memristor in several fields, including Finite time, Projective synchronization, Cellular neural network, Fuzzy logic and Topology.
His Encryption study also includes
- Compressed sensing which intersects with area such as Secure transmission, Matrix multiplication and Matrix,
- Real-time computing which connect with Data transmission, Key space, Overhead, Hash function and Chaotic.
Between 2017 and 2021, his most popular works were:
- Propagation analysis and prediction of the COVID-19 (90 citations)
- Particle swarm optimizer with crossover operation (56 citations)
- Finite-time stability and synchronization of memristor-based fractional-order fuzzy cellular neural networks (55 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Quantum mechanics
- Computer network
Lixiang Li mostly deals with Control theory, Synchronization, Artificial neural network, Memristor and Settling time.
His work on Stability as part of general Control theory research is frequently linked to Simple, bridging the gap between disciplines.
Many of his Synchronization research pursuits overlap with Lyapunov function and Nonlinear system.
His biological study spans a wide range of topics, including Correctness, Algebraic number and Linear matrix.
The concepts of his Memristor study are interwoven with issues in Finite time, Exponential synchronization, System parameters, Cellular neural network and Fuzzy logic.
His studies in Settling time integrate themes in fields like Upper and lower bounds and Synchronization.
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