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The European Physical Journal Special Topics

, Volume 227, Issue 7–9, pp 777–786 | Cite as

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

  • Quan Xu
  • Zhe Song
  • Hui Qian
  • Mo Chen
  • Pingye Wu
  • Bocheng Bao
Regular Article
  • 15 Downloads
Part of the following topical collections:
  1. Nonlinear Effects in Life Sciences

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.

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Copyright information

© EDP Sciences and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Quan Xu
    • 1
  • Zhe Song
    • 1
  • Hui Qian
    • 1
  • Mo Chen
    • 1
  • Pingye Wu
    • 1
  • Bocheng Bao
    • 1
  1. 1.School of Information Science and Engineering, Changzhou UniversityChangzhouP.R. China

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