Global Asymptotic Stability of High-Order Delay Hopfield Neural Networks with Time-Varying Coefficients

2005 ◽  
pp. 419-429 ◽  
Author(s):  
PEIGUANG WANG ◽  
HAIRONG LIAN ◽  
YONGHONG WU
Keyword(s):  
Neural Networks ◽  
Asymptotic Stability ◽  
Global Asymptotic Stability ◽  
High Order ◽  
Hopfield Neural Networks ◽  
Time Varying ◽  
Varying Coefficients ◽  
Time Varying Coefficients

scholarly journals LMI-Based Approach for Exponential Robust Stability of High-Order Hopfield Neural Networks with Time-Varying Delays

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Yangfan Wang ◽  
Linshan Wang
Keyword(s):  
Neural Networks ◽  
Linear Matrix Inequality ◽  
Robust Stability ◽  
High Order ◽  
Hopfield Neural Networks ◽  
Linear Matrix ◽  
Time Varying ◽  
Matrix Inequality ◽  
Global Exponential Robust Stability

This paper studies the problems of global exponential robust stability of high-order hopfield neural networks with time-varying delays. By employing a new Lyapunov-Krasovskii functional and linear matrix inequality, some criteria of global exponential robust stability for the high-order neural networks are established, which are easily verifiable and have a wider adaptive.

Sign in / Sign up

Export Citation Format

Share Document