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This book benefits researchers, engineers, and graduate students in the field of fractional-order complex dynamical networks. Recently, the dynamical behaviors (e.g., passivity, finite-time passivity, synchronization, and finite-time synchronization, etc.) for fractional-order complex networks (FOCNs) have attracted considerable research attention in a wide range of fields, and a variety of valuable results have been reported. In particular, passivity has been extensively used to address the synchronization of FOCNs.
Passivity and finite-time passivity for multi-weighted fractional-order complex networks with fixed and adaptive couplings.- Passivity of coupled fractional-order neural networks with multiple state derivative couplings.- Finite-time passivity for coupled fractional-order neural networks with multi-state or multi-derivative couplings.- Output synchronization analysis and PD control for coupled fractional-order neural networks with multiple weights.- Finite-time output synchronization for fractional-order complex networks with output or output derivative coupling.- Passivity for multiadaptive coupled fractional-order reaction-diffusion neural networks.- Synchronization and adaptive control for coupled fractional-order reaction-diffusion neural networks with multiple couplings.
Jin-Liang Wang (Senior Member, IEEE) received the Ph.D. degree in control theory and control engineering from the School of Automation Science and Electrical Engineering, Beihang University, Beijing, China, in 2014. From 2014 to 2016, he was a lecturer, and from 2017 to 2019, he was an associate professor with the School of Computer Science and Technology, Tiangong University, Tianjin, China, where he has been a professor since 2020. As the first author, he has published three English academic monographs in the Springer and 47 SCI-indexed journal papers (including 33 in Automatica and IEEE Transactions), which have been cited in the SCI-indexed journals by other researchers more than 1500 times. Dr. Wang was a managing guest editor for the Special Issue on Dynamical Behaviors of Coupled Neural Networks With Reaction-Diffusion Terms: Analysis, Control and Applications in the Neurocomputing.


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