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This paper deals with global synchronization in arrays of coupled delayed neural networks with delayed coupling. Through employing Lyapunov-Krasovskii functional and Kronecker product technique, one novel synchronization criterion is presented in terms of linear matrix inequalities(LMIs) based on the integral inequality and convex combination, in which the condition is dependent not only on lower...
In this paper, based on Lyapunov-Krasovskii functional approach and proper integral inequality, one novel sufficient condition is derived to guarantee the global stability for neural networks with interval time-varying delay, in which the general convex combination is employed. The LMI-based criterion heavily depends on the upper and lower bounds on both time delay and its derivative, which is different...
In this letter, simplified delay-dependent stability criteria for neural networks are derived by using a simple integral inequality. The results are in terms of linear matrix inequalities (LMIs) and turn out to be equivalent to some existing results but include less number of LMI variables. This implies that some redundant variables in the existing stability criteria can be removed while maintaining...
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