Research on stability and application of neural network

In order to discuss the stability of neural networks and their performance in practical applications, this paper first reviews the existing stability theories of neural networks, and proposes a Hopfield neural network model on this basis, and uses Lyapunov stability theory to analyze Hopfield neural networks. By constructing energy function as Lyapunov function, the stability of Hopfield neural network in asynchronous updating mode is proved. Through comparative experiments, it is found that the model shows high stability and accuracy on various tasks, which provides strong support for the promotion of neural network in practical applications.