Uniqueness and stability of equilibria of a class of neural networks with applications to the Hopfield model
Zhaoshu Feng, Anthony N. MICHEL · 2002
In this paper, new conditions for the existence and uniqueness of equilibria of a class of continuous-time recurrent neural networks are established by utilizing the Brouwer fixed point theorem and results from homotopy theory. Also, new criteria are established for the local and global asymptotic stability of the equilibrium of neural networks with non-symmetric and symmetric interconnecting matrices, respectively. The present results are applied to the Hopfield continuous-time neural networks.