摘要
在B KOSKO双向联想记忆模型(BAM模型)上,引入了变时滞,去掉了连接权矩阵对称的要求. 利用构造Liaponov泛函,得到了此动力学系统全局渐近稳定的条件. 所得结果,在人工神经网络理论和应用研究中具有实际意义.
In the paper, by use of Liaponov functional analysis, the global asymptotic stability of bi-directional associative memory models (BAM) with variable delays are studied. The obtained results are of important significance in study of theory and application for artificial neural networks.
出处
《上海理工大学学报》
CAS
北大核心
2002年第2期95-97,共3页
Journal of University of Shanghai For Science and Technology
关键词
双向联想记忆神经网络
变时滞
全局渐近稳定性
bi-directional associative memory neural networks
variable delay
global asymptotic stability