Title :
Some stability properties of dynamic neural networks
Author :
Yu, Wen ; Li, XiaoOu
Author_Institution :
Dept. de Control Automatico, CINVESTAV-IPN, Mexico City, Mexico
fDate :
2/1/2001 12:00:00 AM
Abstract :
In this paper, the passivity-based approach is used to derive a tuning algorithm for a class of dynamic neural networks. Several stability properties, such as passivity, asymptotic stability, input-to-state stability and bounded input-bounded output stability, are guaranteed in certain senses
Keywords :
asymptotic stability; neural nets; stability; tuning; asymptotic stability; bounded input-bounded output stability; dynamic neural network; input-to-state stability; passivity; stability properties; tuning algorithm; Asymptotic stability; Circuit stability; Cities and towns; Integrated circuit interconnections; Multilayer perceptrons; Neural networks; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear systems; Stability analysis;
Journal_Title :
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
