Title :
New Delay-Dependent Stability Criteria for Neural Networks With Two Additive Time-Varying Delay Components
Author :
Shao, Hanyong ; Han, Qing-Long
Author_Institution :
Sch. of Electr. & Inf. Autom., Qufu Normal Univ., Rizhao, China
fDate :
5/1/2011 12:00:00 AM
Abstract :
This brief is concerned with delay-dependent stability for neural networks with two additive time-varying delay components. By constructing a new Lyapunov functional and using a convex polyhedron method to estimate the derivative of the Lyapunov functional, some new delay-dependent stability criteria are derived. These stability criteria are less conservative than some existing ones. An example is given to demonstrate the less conservatism of the stability results.
Keywords :
Lyapunov methods; delay systems; neurocontrollers; stability; time-varying systems; Lyapunov functional; additive time-varying delay component; convex polyhedron method; delay-dependent stability criteria; derivative estimation; neural network; Additives; Artificial neural networks; Asymptotic stability; Australia; Delay; Stability criteria; Lyapunov functional; neural networks; stability; time-varying delays; Artificial Intelligence; Computer Simulation; Mathematical Concepts; Models, Theoretical; Neural Networks (Computer); Reaction Time; Time Factors;
Journal_Title :
Neural Networks, IEEE Transactions on
DOI :
10.1109/TNN.2011.2114366