Paper Info
Title
Finite-time and fixed-time anti-synchronization of neural networks with time-varying delays.
Abstract
In this paper, the finite-time and fixed-time anti-synchronization of master-slave dynamical systems with time-varying delays are investigated. The feedback controller is designed only depending on the system state at present time t, but independent of the delayed states, which would be much easier to be verified and realized in practice. Rigorous analysis is developed in two cases with respect to the different ranges of initial state of error systems. Then the absolute value of each error state component can be considered as that, flowing from the initial value to 1 first, then from 1 to 0, and the time it needs in this whole process is finite. As special cases, several neural network models with unbounded time delays are addressed to illustrate the effectiveness and efficiency of our obtained results.
Year
DOI
Venue
2019
10.1016/j.neucom.2018.10.057
Neurocomputing
Keywords
Field
DocType
Neural networks,Finite time,Fixed time,Time delays,Anti-synchronization,Dynamical systems
Fixed time,Synchronization,Feedback controller,Pattern recognition,Absolute value,Control theory,Dynamical systems theory,Initial value problem,Artificial intelligence,Artificial neural network,Mathematics,Finite time
Journal
Volume
ISSN
Citations 
329
0925-2312
5
PageRank 
References 
Authors
0.42
8
2
Name
Order
Citations
PageRank
Lili Wang126913.90
Tianping Chen23095250.77