Title :
Delay-dependent criterion for asymptotic stability of a class of multi-delay neutral equations
Author_Institution :
Inst. of Math. Sci., Inner Mongolia Normal Univ., Huhhot, China
Abstract :
This work gives an improved criterion for asymptotical stability of a class of neural networks described by multi-delay neutral differential equations. Introduced suitable Lyapunov-Krasovskii functional, a delay dependent criterion which not only depends on the discrete delays but also on the neutral delay is presented. The criterion,which can be solved by various efficient convex optimization algorithms, is expressed in terms of linear matrix inequality. In the end of the work, utilizing Matlab toolbox, the numerical example is presented to illustrate feasibility of the criterion given in the work.
Keywords :
Lyapunov methods; asymptotic stability; convex programming; delay systems; differential equations; linear matrix inequalities; neurocontrollers; Lyapunov-Krasovskii functional; Matlab toolbox; asymptotic stability; convex optimization algorithms; delay-dependent criterion; linear matrix inequality; multidelay neutral differential equations; neural networks; neutral type delay systems; Asymptotic stability; Delay; Equations; Linear matrix inequalities; Numerical stability; Stability criteria; Asymptotic Stability; LMI Approach; Multi-delay; Neural Network; Neutral Differential Equations;
Conference_Titel :
Control Conference (CCC), 2010 29th Chinese
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-6263-6