Texas A&M University at Qatar
Dynamics and Analysis of Coupled Reation-Diffusion Neural Networks
This talk focuses on dynamical analysis of coupled reation-diffusion neural networks (CRDNN). Since neural networks are implemented by electric circuits, and the diffusion phenomena inevitably appear in electric circuits once electrons transport in a non-uniform electromagnetic field. It is critical to investigate the diffusional phenomena in coupled neural networks. We will discuss the dynamics such as the stability, synchronization, passivity of the neural networks with reaction-diffusion, and present several effective and powerful strategies such as adaptive strategy for the CRDNN reaching synchronization.
Prof. Tingwen Huang's research focuses on dynamics of nonlinear systems including neural networks, complex networks and multi-agent and their applications to smart grids and cybersecurity. He has published 4 monographs, 600+ journal papers and conference proceedings including 250 papers in IEEE Transactions journals. He has been listed annually as the Highly Cited Researcher by Clarivate Analytics, formerly Thomson Reuters since 2018. His research has been continuously supported by Qatar National Research Fund (QNRF) with more than 7 million US dollars in total. One of his projects was awarded the Best Research Project Award by QNRF in 2015.
He is the first recipient of Dean’s Fellow for Recognition of Faculty’s Excellence and Achievements awarded by Texas A&M University at Qatar (TAMUQ) in 2014, was bestowed Faculty Research Excellence Award by TAMUQ in 2015, was elected as IEEE Fellow in 2018, conferred Changjiang Chair Professor in 2019 by Ministry of Education of China, was elected as Academician of the International Academy for Systems and Cybernetic Sciences recently.