Global Exponential Stability of Reaction-Diffusion Hopfield Neural Networks with Distributed Delays

摘要

The global exponential stability of reaction-diffusion Hopfield neural networks with distributed delays is studied. Without assuming the boundedness, monotonicity and differentiability of the activation functions, the sufficient conditions were obtained by utilizing Dini's derivative, F-function and extended Hanaly's inequality. These conditions are easy to check and apply in practice and can be regarded as an extension of existing results.