کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
406374 | 678081 | 2015 | 9 صفحه PDF | دانلود رایگان |
In this paper, we are concerned with a class of high-order neural networks (HONNs) with nonsmooth activation functions. A set of new sufficient conditions ensuring the coexistence of 3n3n equilibrium points and the local stability of 2n2n equilibrium points are proposed, which reveal that the high-order interactions between neurons also play an important role on the multistability of HONNs. Besides, every solution is shown to converge to a certain equilibrium point, that is, the systems are also completely stable. Furthermore, for the 2-neuron neural networks, we can get that the stable manifolds of unstable equilibrium points constitute the boundaries of attraction basins of stable equilibrium points, despite the nonlinearity of high-order items of HONNs. Several numerical examples are presented to illustrate the effectiveness of our criteria.
Journal: Neurocomputing - Volume 152, 25 March 2015, Pages 222–230