TY - JOUR
T1 - Recent Advances on Dynamical Behaviors of Coupled Neural Networks with and without Reaction-Diffusion Terms
AU - Wang, Jin Liang
AU - Qiu, Shui Han
AU - Chen, Wei Zhong
AU - Wu, Huai Ning
AU - Huang, Tingwen
N1 - Publisher Copyright:
© 2012 IEEE.
PY - 2020/12
Y1 - 2020/12
N2 - 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.
AB - 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.
KW - Coupled neural networks (CNNs)
KW - coupled reaction-diffusion neural networks
KW - passivity
KW - stability
KW - synchronization
UR - https://www.scopus.com/pages/publications/85086888032
U2 - 10.1109/TNNLS.2020.2964843
DO - 10.1109/TNNLS.2020.2964843
M3 - 文章
C2 - 32175875
AN - SCOPUS:85086888032
SN - 2162-237X
VL - 31
SP - 5231
EP - 5244
JO - IEEE Transactions on Neural Networks and Learning Systems
JF - IEEE Transactions on Neural Networks and Learning Systems
IS - 12
M1 - 9037199
ER -