版权说明 操作指南
首页 > 成果 > 详情

Global exponential stability of cohen-grossberg neural networks with time-varying delays

认领
导出
反馈
分享
QQ微信 微博
成果类型:
期刊论文
作者:
X. Wang;X. Li;W. Zhou
通讯作者:
Li, X.
作者机构:
College of Science, Hunan Agricultural University, Changsha, Hunan, 410128, China
通讯机构:
College of Science, Hunan Agricultural University, Changsha, Hunan, China
语种:
英文
关键词:
Cohen-Grossberg neural networks;Global exponential stability;M-matrix;Nonlinear measure;Time-varying delays;Unique equilibrium
期刊:
Italian Journal of Pure and Applied Mathematics
ISSN:
2239-0227
年:
2018
期:
40
页码:
126-140
机构署名:
本校为第一且通讯机构
院系归属:
理学院
摘要:
In this paper, without the assumptions for boundedness, monotonicity, and differentiability on activation functions and symmetry of interconnections, a class of Cohen-Grossberg neural networks with time-varying delays is studied. A new useful criteria on the uniqueness of equilibrium is obtained by utilizing the nonlinear measure. Combining with Dini derivatives and Young inequality, new sufficient condition for the global exponential stability is established by directly estimating the upper bound of solutions of the system. All results are pre...

反馈

验证码:
看不清楚,换一个
确定
取消

成果认领

标题:
用户 作者 通讯作者
请选择
请选择
确定
取消

提示

该栏目需要登录且有访问权限才可以访问

如果您有访问权限,请直接 登录访问

如果您没有访问权限,请联系管理员申请开通

管理员联系邮箱:yun@hnwdkj.com