%0 Journal Article
%T Improved Exponential Bidirectional Associative Memory and Its Performance Evaluation<br>改进的指数双向联想记忆模型及性能估计
%A CHEN Song-can
%A GAO Hang
%A <br>陈松灿
%A 高航
%J 软件学报
%D 1999
%I 
%X In this paper, a new improved exponential bidirectional associative memory (IeBAM) model is proposed. Its stability in synchronous and asynchronous updating modes of the states is proven by defining an energy function which is bounded and decreases as the states change. On one hand, IeBAM eliminates the unreasonable hypotheses in the stability proofs of both Wang's modified exponential BAM (MeBAM) and Jeng's exponential BAM (eBAM). On the other hand, it relaxes the continuity assumption of the BAM (bidirectional associative memory) and avoids the complement encoding problem. The theoretical analysis and computer simulations indicate that the IeBAM has higher storage capacity and better error-correcting capability than the MeBAM and the eBAM.
%K Neural networks
%K (exponential) associative memories
%K stability
%K bidirectionality
%K performance evaluation<br>神经网络
%K （指数）联想记忆
%K 稳定性
%K 双向性
%K 性能估计.
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=7735F413D429542E610B3D6AC0D5EC59&aid=41A83F8752F3B831&yid=B914830F5B1D1078&vid=F3090AE9B60B7ED1&iid=E158A972A605785F&sid=BFB86B6ED3A99B9D&eid=5335AD3CFE6E14EA&journal_id=1000-9825&journal_name=软件学报&referenced_num=4&reference_num=8