LMI approach to robust stability analysis of Hopfield neural networks

Authors:	Ji Ce, Northeastern University, China Zhang Hua-guang, Northeastern University, China
Topic:	2.5 Robust Control
Session:	Robustness Analysis II
Keywords:	neural networks; delay; perturbation; robust stability; Lyapunov functional

Abstract

The robust stability of a class of Hopfield neural networks with multiple delays and parameter perturbations is analyzed. The sufficient conditions for the global robust stability of equilibrium point are given by way of constructing a suitable Lyapunov-Krasovskii functional. The conditions take the form of linear matrix inequality (LMI), so they are computationally efficient. In addition, the results are independent of delays and established without assuming differentiability and monotonicity of activation functions.