Passivity and stability analysis of neural networks with time-varying delays via extended free-weighting matrices integral inequality

2018 ◽  
Vol 106 ◽  
pp. 67-78 ◽  
Author(s):  
M.J. Park ◽  
O.M. Kwon ◽  
J.H. Ryu
Keyword(s):  
Neural Networks ◽  
Stability Analysis ◽  
Integral Inequality ◽  
Time Varying ◽  
Passivity And Stability Analysis

scholarly journals On Less Conservative Stability Criteria for Neural Networks with Time-Varying Delays Utilizing Wirtinger-Based Integral Inequality

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
O. M. Kwon ◽  
M. J. Park ◽  
Ju H. Park ◽  
S. M. Lee ◽  
E. J. Cha
Keyword(s):  
Neural Networks ◽  
Stability Analysis ◽  
Integral Inequality ◽  
Linear Matrix ◽  
Time Varying ◽  
Matrix Inequalities ◽  
Stability Criteria ◽  
Numerical Examples ◽  
Maximum Delay ◽  
Delay Dependent

This paper investigates the problem of stability analysis for neural networks with time-varying delays. By utilizing the Wirtinger-based integral inequality and constructing a suitable augmented Lyapunov-Krasovskii functional, two less conservative delay-dependent criteria to guarantee the asymptotic stability of the concerned networks are derived in terms of linear matrix inequalities (LMIs). Three numerical examples are included to explain the superiority of the proposed methods by comparing maximum delay bounds with the recent results published in other literature.

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