New results on asymptotic stability analysis for static recurrent neural networks

摘要

This paper focuses on the asymptotic stability analysis for static recurrent neural networks. Simplified stability criteria for static neural networks are obtained and augmented Lyapunov functionals are introduced to study the delay-dependent stability for systems. Numerical examples show the improvement over approaches in the literature.