In this paper, we study the stability and Hopf bifurcation of a class of six-neuron fractional BAM neural networks with multiple delays. Firstly, the model is transformed into a fractional neural network model with two nonidentical delays by using variable substitution. Then, by assigning a value to one of the time delays and selecting the remaining time delays as parameters, the critical value of Hopf bifurcation for different time delays is calculated. The study shows that when the time lag exceeds its critical value, the equilibrium point of the system will lose its stability and generate H...
