论文标题
与边界反馈的2D细胞神经网络的指数同步
Exponential Synchronization of 2D Cellular Neural Networks with Boundary Feedback
论文作者
论文摘要
In this work we propose a new model of 2D cellular neural networks (CNN) in terms of the lattice FitzHugh-Nagumo equations with boundary feedback and prove a threshold condition for the exponential synchronization of the entire neural network through the \emph{a priori} uniform estimates of solutions and the analysis of dissipative dynamics.网络的成对边界单元之间的间隙信号所满足的阈值由结构参数表示，并且可调节。本文的新结果和方法也可以推广到3D和更高维度的Fitzhugh-Nagumo类型或Hindmarsh-Rose型细胞神经网络。
In this work we propose a new model of 2D cellular neural networks (CNN) in terms of the lattice FitzHugh-Nagumo equations with boundary feedback and prove a threshold condition for the exponential synchronization of the entire neural network through the \emph{a priori} uniform estimates of solutions and the analysis of dissipative dynamics. The threshold to be satisfied by the gap signals between pairwise boundary cells of the network is expressed by the structural parameters and adjustable. The new result and method of this paper can also be generalized to 3D and higher dimensional FitzHugh-Nagumo type or Hindmarsh-Rose type cellular neural networks.
