个人信息
沙春林
性别:男
联系方式:shachunlin@nuaa.edu.cn 学位:博士

个人信息 Personal information

学历:博士毕业 毕业院校:南京航空航天大学 所在单位:理学院 职务:教师 办公地点:数学学院三楼 电子邮箱:

Design and analysis of associative memories based on external inputs of continuous bidirectional associative networks

点击次数: 所属单位:理学院 发表刊物:NEUROCOMPUTING 关键字:Associative memories External inputs Design methods Network dynamics Globally exponential stability 摘要:This paper presents an extended continuous bidirectional associative memory network (CBAM) and a new ring recurrent network to behave as associative memories with external inputs. The proposed networks are robust in terms of design parameter selection. Some globally exponential stable criteria are derived for the networks with high storage capacity. The approach, by generating networks where the input data are fed via external inputs rather than initial conditions, enables multiple prototype patterns to be retrieved simultaneously. The results improve and extend some previous related works. Recurring to the numerical method, several applicable examples are given to illustrate the effectiveness of the proposed networks. (C) 2017 Elsevier B.V. All rights reserved. ISSN号:0925-2312 是否译文: 发表时间:2017-11-29 合写作者:赵洪涌 通讯作者:沙春林,赵洪涌