Abstract
Owing to the influence of factors such as signal transmission delay, external interference and parameter deviation, the stability of neural networks has always been the focus of scholars, and many related literatures have been published. This article mainly summarises and analyses the stability research of several types of neural networks (Hopfield neural network, BAM neural network, cellular neural network, Cohen-Grossberg neural network). In the study of neural network stability, in addition to the common methods such as Lyapunov-Krasovskii method and LMI technology, other more advantageous solutions are also analysed. Finally, the conclusion and prospect of neural network stability analysis are given.
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