Stability Analysis on Cohen–Grossberg Neural Networks with Saturated Impulse Inputs

摘要

This paper aims to analyze the stability of Cohen–Grossberg neural networks with saturated impulse inputs. By using the method of Lyapunov functions, convex analysis and matrix inequality, some sufficient conditions are obtained to ensure the stability of the Cohen–Grossberg networks with saturated impulse inputs, including full state constraints and partial state constraints. And some conservative corollaries are obtained. In addition, the fixed time-delay network with fixed impulsive inputs is analyzed by the similar method. Meanwhile, the effectiveness and validity are verified by some numerical examples.