DocumentCode
3269839
Title
Fault accommodation for complete synchronization of complex neural networks
Author
Zhanshan Wang ; Fufei Chu ; Hongjing Liang ; Huaguang Zhang
Author_Institution
Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
fYear
2013
fDate
16-19 April 2013
Firstpage
200
Lastpage
205
Abstract
This paper is concerned with the adaptive fault tolerant synchronization problem for a class of complex interconnected neural networks against sensor failure and coupling failure. As sensor and coupling failure may lead to performance degradation or even instability of the whole network, adaptive approach is proposed to adjust unknown coupling factors for the deteriorated network compensations, as well as to estimate controller parameters to compensate the effects of failed coupling. Through Lyapunov functions and adaptive schemes, three kind of fault tolerant controllers are constructed to ensure the synchronization of the networks in the presence of the network deterioration. Simulation results are given to verify the effectiveness of the proposed method.
Keywords
Lyapunov methods; complex networks; controllers; failure analysis; fault tolerance; interconnected systems; neural nets; parameter estimation; sensors; synchronisation; Lyapunov functions; adaptive fault tolerant synchronization problem; adaptive schemes; complex interconnected neural network synchronization; controller parameter estimation; coupling factors; coupling failure; deteriorated network compensations; fault accommodation; fault tolerant controllers; performance degradation; sensor failure; Adaptive systems; Complex networks; Couplings; Fault tolerance; Fault tolerant systems; Symmetric matrices; Synchronization;
fLanguage
English
Publisher
ieee
Conference_Titel
Adaptive Dynamic Programming And Reinforcement Learning (ADPRL), 2013 IEEE Symposium on
Conference_Location
Singapore
ISSN
2325-1824
Type
conf
DOI
10.1109/ADPRL.2013.6615008
Filename
6615008
Link To Document