Title :
Exponential Stability Analysis for Neural Networks With Time-Varying Delay
Author :
Wu, Min ; Liu, Fang ; Shi, Peng ; He, Yong ; Yokoyama, Ryuichi
Author_Institution :
Sch. of Inf. Sci. & Eng., Central South Univ., Changsha
Abstract :
This correspondence paper focuses on the problem of exponential stability for neural networks with a time-varying delay. The relationship among the time-varying delay, its upper bound, and their difference is taken into account. As a result, an improved linear-matrix-inequality-based delay-dependent exponential stability criterion is obtained without ignoring any terms in the derivative of Lyapunov-Krasovskii functional. Two numerical examples are given to demonstrate its effectiveness.
Keywords :
Lyapunov methods; delays; linear matrix inequalities; neural nets; stability criteria; time-varying systems; Lyapunov-Krasovskii functional; delay-dependent exponential stability criterion; exponential stability analysis; linear matrix inequality; neural networks; time-varying delay; Exponential stability; linear matrix inequality (LMI); neural networks; time-varying delay; Algorithms; Computer Simulation; Models, Theoretical; Neural Networks (Computer);
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
DOI :
10.1109/TSMCB.2008.915652