STABILITY ANALYSIS OF BRAIN-STATE-IN-A-BOX NEURAL NETWORKS
盒中脑神经网络的稳定性分析

This paper presents a novel asymptotical stability analysis of the equilibrium points in the unit hypercube for the Brain-State-in-a-Box neural model. Some sufficient conditions for the asymptotical stability of equilibrium points are derived using Ostrowski's theorem and the similarity transformation approach. Simulation examples are given to illustrate the effectiveness of new analysis method.