%0 Journal Article
%T EXPONENTIAL STABILITY OF CONTINUOUS BAM NEURAL NETWORK<br>连续型BAM神经网络的指数稳定性
%A Cong JIN
%A <br>金聪
%J 系统科学与数学
%D 2001
%I 
%X In this paper, the continuous bidirectional associative memory(BAM) neural networks can be considered as a special Hopfield network model. A novel exponential stability analysis is presented for the equilibrium points of continuous BAM neural networks. A constraint condition on the connection matrix has been found under which the neural network has a unique equilibrium point. The analysis in this paper can be used to design globally exponentially stable neural networks.
%K Neural networks
%K bidirectional associative memory
%K exponential stability<br>神经网络
%K 双向联想记忆(BAM)
%K 指数稳定性.
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=6E709DC38FA1D09A4B578DD0906875B5B44D4D294832BB8E&cid=37F46C35E03B4B86&jid=0CD45CC5E994895A7F41A783D4235EC2&aid=8275BDCF1A835460&yid=14E7EF987E4155E6&vid=659D3B06EBF534A7&iid=38B194292C032A66&sid=5957D6E0A50D26B5&eid=15251AE9C02726D3&journal_id=1000-0577&journal_name=系统科学与数学&referenced_num=1&reference_num=9