摘要
该文对盒中脑(BSB)神经网络在超立方体内的平衡点的渐近稳定性进行了新的分析,利用Ostrowski定理及相似变换得到了判定平衡点为渐近稳定的几个充分条件。为了说明所提出新方法的有效性,给出了模拟例子。
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.
关键词
神经网络
盒中脑
渐近稳定性
人工智能
Neural networks, Brain-State-in-a-Box, Asymptotic stability
