Title :
Global exponential stability of complex-valued neural networks with time-varying delays on time scales
Author :
Zhao Zhenjiang ; Song Qiankun
Author_Institution :
Dept. of Math., Huzhou Teachers Coll., Huzhou, China
Abstract :
In this paper, the global exponential stability of complex-valued neural networks (CVNN) with time-varying delays is investigated. By constructing appropriate Lyapunov-Krasovskii functionals and using matrix inequality technique, a new delay-dependent criterion for checking the global exponential stability of the addressed CVNN is established in terms of linear matrix inequalities (LMIs), which can be checked numerically using the effective LMI toolbox in MATLAB. An example with simulations is given to show the effectiveness of the proposed criterion.
Keywords :
Lyapunov methods; asymptotic stability; delay systems; linear matrix inequalities; neurocontrollers; time-varying systems; CVNN; LMI toolbox; LMIs; Lyapunov-Krasovskii functionals; Matlab; complex-valued neural networks; delay-dependent criterion; global exponential stability; linear matrix inequalities; matrix inequality technique; time scales; time-varying delays; Biological neural networks; Control theory; Delays; Stability criteria; Complex-Valued Neural Networks; Global Exponential Stability; Linear Matrix Inequality; Time Scales; Time-Varying Delay;
Conference_Titel :
Control Conference (CCC), 2014 33rd Chinese
Conference_Location :
Nanjing
DOI :
10.1109/ChiCC.2014.6895804