Passivity Analysis of Dynamic Neural Networks with Different Time-scales

被引：0
|
作者：
Wen Yu
Xiaoou Li
机构：
[1] CINVESTAV-IPN,Departamento de Control Automatico
[2] CINVESTAV-IPN,Departamento de Computación
来源：
Neural Processing Letters | 2007年 / 25卷
关键词：
different time scales; neural networks; passivity; stability;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Dynamic neural networks with different time-scales include the aspects of fast and slow phenomenons. Some applications require that the equilibrium points of the designed networks are stable. In this paper, the passivity-based approach is used to derive stability conditions for dynamic neural networks with different time-scales. Several stability properties, such as passivity, asymptotic stability, input-to-state stability and bounded input bounded output stability, are guaranteed in certain senses. A numerical example is also given to demonstrate the effectiveness of the theoretical results.
引用
收藏
页码：143 / 155
页数：12
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