H∞ state estimation for discrete-time neural networks with interval time-varying delays and probabilistic diverging disturbances

2015 ◽  
Vol 153 ◽  
pp. 255-270 ◽  
Author(s):  
M.J. Park ◽  
O.M. Kwon ◽  
Ju H. Park ◽  
S.M. Lee ◽  
E.J. Cha
2013 ◽  
Vol 2013 ◽  
pp. 1-14 ◽  
Author(s):  
M. J. Park ◽  
O. M. Kwon ◽  
Ju H. Park ◽  
S. M. Lee ◽  
E. J. Cha

The purpose of this paper is to investigate a delay-dependent robust synchronization analysis for coupled stochastic discrete-time neural networks with interval time-varying delays in networks coupling, a time delay in leakage term, and parameter uncertainties. Based on the Lyapunov method, a new delay-dependent criterion for the synchronization of the networks is derived in terms of linear matrix inequalities (LMIs) by constructing a suitable Lyapunov-Krasovskii’s functional and utilizing Finsler’s lemma without free-weighting matrices. Two numerical examples are given to illustrate the effectiveness of the proposed methods.


2008 ◽  
Vol 72 (1-3) ◽  
pp. 643-647 ◽  
Author(s):  
Shaoshuai Mou ◽  
Huijun Gao ◽  
Wenyi Qiang ◽  
Zhongyang Fei

2014 ◽  
Vol 131 ◽  
pp. 171-178 ◽  
Author(s):  
A. Arunkumar ◽  
R. Sakthivel ◽  
K. Mathiyalagan ◽  
S. Marshal Anthoni

2013 ◽  
Vol 99 ◽  
pp. 188-196 ◽  
Author(s):  
M.J. Park ◽  
O.M. Kwon ◽  
Ju H. Park ◽  
S.M. Lee ◽  
E.J. Cha

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