TY - JOUR
T1 - Global dynamics of periodic delayed neural networks models
AU - Zhou, Jin
AU - Liu, Zengrong
AU - Chen, Guanrong
PY - 2005/10
Y1 - 2005/10
N2 - In this paper, without assuming the smoothness, monotonicity and bounded-ness of the activation functions, some new and simple sufficient conditions of the existence and global exponential stability of periodic attractors for a model of periodic delayed recurrent neural networks are obtained by utilizing topological degree theory and the Lyapunov functional methods, which are natural extension and generalization of the corresponding results existing in the literature. Copyright © 2005 Watam Press.
AB - In this paper, without assuming the smoothness, monotonicity and bounded-ness of the activation functions, some new and simple sufficient conditions of the existence and global exponential stability of periodic attractors for a model of periodic delayed recurrent neural networks are obtained by utilizing topological degree theory and the Lyapunov functional methods, which are natural extension and generalization of the corresponding results existing in the literature. Copyright © 2005 Watam Press.
KW - Dynamic attractor
KW - Lyapunov functional
KW - Periodic delayed recurrent neural networks
KW - Periodic solutions
KW - Stability
KW - Topological degree theory
UR - http://www.scopus.com/inward/record.url?scp=28744439312&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-28744439312&origin=recordpage
M3 - RGC 21 - Publication in refereed journal
SN - 1492-8760
VL - 12
SP - 689
EP - 699
JO - Dynamics of Continuous, Discrete and Impulsive Systems Series B: Applications and Algorithms
JF - Dynamics of Continuous, Discrete and Impulsive Systems Series B: Applications and Algorithms
IS - 5-6
ER -