Input-to-state stability (ISS) analysis for dynamic neural networks 论文
1999IEEE Transactions on Circuits and Systems I Fundamental Theory and Applications引用 321
Neural Networks and ApplicationsAdaptive Control of Nonlinear SystemsNeural Networks Stability and Synchronization
详细信息
- 发表期刊/会议
- IEEE Transactions on Circuits and Systems I Fundamental Theory and Applications
- 发表日期
- 1999-01-01
- 发表年份
- 1999
关键词
Neural Networks and ApplicationsAdaptive Control of Nonlinear SystemsNeural Networks Stability and Synchronization
摘要
In this paper a novel approach to assess the stability of dynamic neural networks is presented. Using a Lyapunov function, we determine conditions to guarantee input-to-state stability (ISS) which also ensures global asymptotic stability (GAS). The applicability of these conditions is illustrated by two examples.