SCALE-TYPE STABILITY FOR NEURAL NETWORKS WITH UNBOUNDED TIME-VARYING DELAYS

• 作者: Liangbo Chen Zhenkun Huang
• 来源期刊: 应用数学年刊：英文版
• 学科: 数学
• 关键词: GLOBAL ASYMPTOTIC STABILITY GLOBAL EXPONENTIAL STABILITY neural networks on time scales
• 年，卷（期）: 2016,（3）
• 页码范围: 234-248
• 页数: 15页
• 分类号: O1

摘要

This paper studies scale-type stability for neural networks with unbounded time-varying delays and Lipschitz continuous activation functions. Several sufficient conditions for the global exponential stability and global asymptotic stability of such neural networks on time scales are derived. The new results can extend the existing relevant stability results in the previous literatures to cover some general neural networks.