Recent Advances on Dynamical Behaviors of Coupled Neural Networks With and Without Reaction-Diffusion Terms.

abstract

• Recently, the dynamical behaviors of coupled neural networks (CNNs) with and without reaction-diffusion terms have been widely researched due to their successful applications in different fields. This article introduces some important and interesting results on this topic. First, synchronization, passivity, and stability analysis results for various CNNs with and without reaction-diffusion terms are summarized, including the results for impulsive, time-varying, time-invariant, uncertain, fuzzy, and stochastic network models. In addition, some control methods, such as sampled-data control, pinning control, impulsive control, state feedback control, and adaptive control, have been used to realize the desired dynamical behaviors in CNNs with and without reaction-diffusion terms. In this article, these methods are summarized. Finally, some challenging and interesting problems deserving of further investigation are discussed.

authors

• Huang, Tingwen

published proceedings

• IEEE Trans Neural Netw Learn Syst

author list (cited authors)

• Wang, J., Qiu, S., Chen, W., Wu, H., & Huang, T.

citation count

• 21

complete list of authors

• Wang, Jin-Liang||Qiu, Shui-Han||Chen, Wei-Zhong||Wu, Huai-Ning||Huang, Tingwen

publication date

• December 2020

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• IEEE Transactions on Neural Networks and Learning Systems  Journal

keywords

• Algorithms
• Feedback
• Fuzzy Logic
• Neural Networks, Computer
• Stochastic Processes
• Uncertainty

Digital Object Identifier (DOI)

• 10.1109/TNNLS.2020.2964843

start page

• 5231

end page

• 5244

volume

• 31

issue

• 12

URL

• http://dx.doi.org/10.1109/tnnls.2020.2964843