Analysis of the equilibrium points of background neural networks with uniform firing rate
Fang Xu, Lingling Liu, Jianying Xiao · Advances in Difference Equations · 2017
In this paper, we give a complete analysis of the equilibrium points of background neural networks with uniform firing rates. By using continuity, monotonicity of some functions and Rolle’s theorem, the number of equilibrium points and their locations are obtained. Moreover, some novel sufficient conditions are given to guarantee the stability of the equilibrium points for the network model by utilizing Taylor’s theorem. A simulation example is conducted to illustrate the theories developed in this paper.