Exponential stability and global stability of cellular neural networks

摘要

In this paper, we present two types of matrix stability: complete stability and strong stability, and some properties of them. By using these properties, we discuss stability of cellular neural networks and obtain some conditions ensuring uniqueness, exponential stability and global asymptotic stability of the equilibrium point for cellular neural networks. In particular, in the two-cell case, the network is globally exponentially stable if and only if the feedback matrix minus the unit matrix is a complete stable matrix.