Novel exponential stability criteria of high-order neural networks with time-varying delays.
The global exponential stability is analyzed for a class of high-order Hopfield-type neural networks with time-varying delays. Based on the Lyapunov stability theory, together with the linear matrix inequality approach and free-weighting matrix method, some less conservative delay-independent and delay-dependent sufficient conditions are presented for the global exponential stability of the equilibrium point of the considered neural networks. Two numerical examples are provided to demonstrate the effectiveness of the proposed stability criteria.
Zheng
Cheng-De
CD
Department of Mathematics, Dalian Jiaotong University, Dalian 116028, China. zhengchengde@dl.cn
Zhang
Huaguang
H
Wang
Zhanshan
Z
D000465:Algorithms; D003198:Computer Simulation; D003661:Decision Support Techniques; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated / Q000379:methods*