Paper Info
Title
Finite-time synchronization of fractional-order memristive recurrent neural networks with discontinuous activation functions.
Abstract
This paper is concerned with the finite-time synchronization for a class of drive-response fractional-order memristive recurrent neural networks with discontinuous activation functions. By using the theories of fractional-order differential inclusions and set-valued map, the finite-time synchronization problem for a class of drive-response fractional-order memristive recurrent neural networks with discontinuous activation functions is formulated under the framework of Filippov solution. Then, two novel state feedback controllers are designed according to state feedback control technique. In particular, based on the fractional Lyapunov stability theory, the finite-time stability theory and Young inequality, some novel algebraic synchronization criteria are obtained to ensure the finite-time synchronization of a class of drive-response fractional-order memristive recurrent neural networks with discontinuous activation functions. Moreover, we give the estimation of the upper bound of the settling time for synchronization. Finally, a simulation example is given to show the effectiveness of our theoretical results.
Year
DOI
Venue
2018
10.1016/j.neucom.2018.08.003
Neurocomputing
Keywords
Field
DocType
Memristive recurrent neural networks,Finite-time synchronization,Discontinuous activation functions,State feedback control
Differential inclusion,Topology,Young's inequality,Synchronization,Pattern recognition,Settling time,Upper and lower bounds,Lyapunov stability,Recurrent neural network,Artificial intelligence,Mathematics,Stability theory
Journal
Volume
ISSN
Citations 
316
0925-2312
5
PageRank 
References 
Authors
0.40
31
4
Name
Order
Citations
PageRank
xiaofan li17912.44
Jianán Fang221516.62
Wenbing Zhang353723.91
Huiyuan Li4413.53