Eur. Phys. J. Special Topics 227, 777–786 (2018)
https://doi.org/10.1140/epjst/e2018-700122-3

Regular Article

Numerical analyses and breadboard experiments of twin attractors in two-neuron-based non-autonomous Hopfield neural network

School of Information Science and Engineering, Changzhou University, Changzhou 213164, P.R. China

^a e-mail: mervinbao@126.com

Received: 17 November 2017
Received in final form: 16 December 2017
Published online: 19 October 2018

Abstract

This paper investigates twin attractors in a two-neuron-based non-autonomous Hopfield neural network (HNN) through numerical analyses and hardware experiments. Stability analysis of the DC equilibrium point is executed and an unstable saddle-focus is found in the parameter region of interest. The stimulus-associated dynamical behaviors are numerically explored by bifurcation diagrams and dynamical map in two-dimensional parameter-space, from which coexisting twin attractors behavior can be observed with the variations of two stimulus-associated parameters. Moreover, breadboard experiment investigations are carried out, which effectively verify the numerical simulations.