Multistability of neural networks with discontinuous activation function

Abstract

In this paper, the multistability is studied for two-dimensional neural networks with multilevel activation functions. And it is showed that the system has n2 isolated equilibrium points which are locally exponentially stable, where the activation function has n segments. Furthermore, evoked by periodic external input, n2 periodic orbits which are locally exponentially attractive, can be found. And these results are extended to k-neuron networks, which is really enlarge the capacity of the associative memories. Examples and simulation results are used to illustrate the theory.

Gan Huang

My research interests include Neural Modulation, Brain Computer Interface and Neural Prosthetics.