Dynamics of class of 2-D neural networks
一类二维神经网络的动力学研究

Multistability of neural networks have attracted much interests of scientists. Since the monostable networks were computationally restricted, so the analysis for multistable networks became necessary. In this paper, they investigated complex dynamical behaviors of a class of 2-D neural networks. Firstly, by the use of contradiction, an invariant set was obtained so that the trajectories of neural networks originated from the set would enter it for ever. The existence of the interior equilibrium point was proved by constructing a closed curve and using the winding number of the vector field. Furthermore, the boundedness of the networks by using contradiction was proved. Finally, digital simulations were carried to validate the findings.